Information Research an international electronic journal
Information Research is a freely available, international, scholarly journal, dedicated to making accessible the results of research across a wide range of information-related disciplines.
Preface, Organisation, Reviewers, and Table of content
The iConference is a testimony to the resilience, adaptability, and innovation of the information community. As digital infrastructures increasingly shape how we learn, communicate, govern, and remember, the iConference offers a space to explore what it means to be digitally literate and ethically informed. At iConference 2026, the iSchools community has examined the ethical, social, political, and cultural dimensions of information to inspire and explore new areas of research.
Copyright (c) 2026 Isaac Sserwanga, Hanna Carlsson, Yuxiang (Chris) Zhao, Douglas W. Oard, Jennifer Campbell-Meier, Heinz Pampel, Jessica Barfield, Julián D. Cortés, Fernanda Ribeiro, Eduardo Vendrell Vidal, Brasilina Passarelli https://creativecommons.org/licenses/by-nc/4.0
Information seeking behavior of agricultural professionals from developing countries in South Korea
Introduction. This study investigates the information seeking behavior (ISB) of agricultural professionals from developing countries in South Korea. Anchored in Leckie, Pettigrew, and Sylvain’s (1996) professional ISB model, it examines how roles, tasks, and contextual factors shape information needs, source awareness, and use outcomes. Method. A qualitative design was employed, using semi-structured interviews with ten professionals from government agricultural agencies on study leave in South Korea. Participants represented extension, research, laboratory services, policy, education, and specialized production. Analysis. Transcripts were thematically coded following Strauss and Corbin, with categories mapped to the six components of the Leckie et al.’s (1996) model. Comparative analysis highlighted recurring patterns and contextual variations. Results. Information needs varied by role: extension workers required technical packages; researchers, precise standards, and datasets; educators, pedagogically validated materials; policymakers, authoritative frameworks; and specialists, scientific and local knowledge. Formal sources (bulletins, standards, literature) and informal channels (colleagues, networks, digital tools) were both critical. Exposure to South Korea’s infrastructures expanded participants’ awareness of alternative systems. Conclusion(s). The study extends Leckie et al.’s model by showing how infrastructural constraints and cross-border experiences condition ISB, with implications for designing user-centered, context-sensitive systems.
Copyright (c) 2026 Ana Mae Cantel, Eun Youp Rha https://creativecommons.org/licenses/by-nc/4.0
Exploring metacognitive regulation activities and their roles in prompt literacy development among humanities and social science researchers in GenAI
Introduction. Generative artificial intelligence (GenAI) has profoundly influenced research paradigms in the humanities and social sciences (HSS) while imposing greater demands on users’ prompt literacy. There is an urgent need for empirical inquiry into how HSS researchers leverage metacognitive regulation activities to develop prompt literacy. Method. Seventeen HSS researchers were recruited to participate in semi-structured interviews designed to examine their metacognitive activities and prompting behaviors when interacting with GenAI and to explore the role of metacognition in developing prompt literacy. Analysis. The interview data were analysed using thematic analysis, with initial coding and theme identification conducted through iterative clustering. Results. Our research shows that metacognitive regulation activities—planning, monitoring and evaluation—enhance prompt literacy in HSS researchers through four distinct stages. Prompt literacy manifests as a normative attitude toward prompts, the ability to design prompts, the ability to evaluate prompts, and the ability to think critically about prompting. Conclusions. These findings reveal how metacognitive regulation shapes prompt literacy and provide theoretical and practical insights for cultivating prompt literacy in the GenAI era.
Copyright (c) 2026 Yutian Jing , Yuxiang Chris Zhao , Durong Wang , Siqi Liu , Qinghua Zhu https://creativecommons.org/licenses/by-nc/4.0
AI-assisted writing's differential impact on EFL learners and implications for adaptive instruction
Introduction. While AI-assisted writing tools gain widespread educational adoption, their differential impacts on English as a foreign language (EFL) learners across proficiency levels remain underexplored. This study investigates how AI writing assistance affects EFL learners at different proficiency levels to inform differentiated instructional design. Method. A controlled experiment with 17 Chinese university students divided into low-, intermediate-, and high-proficiency groups employed mixed methods, analyzing 85 writing samples and 56 human-AI interaction dialogues using SPSS and NVivo. Analysis. Findings revealed striking proficiency-dependent effects: low-proficiency learners showed significant writing improvements after AI-assisted training, while intermediate- and high-proficiency learners demonstrated minimal gains. Interaction analysis uncovered distinct usage patterns—low- and intermediate-proficiency learners relied on AI primarily for linguistic compensation, whereas high-proficiency learners engaged in extensive prompt refinement to align AI output with their writing goals. Conclusion(s). Results challenge one-size-fits-all approaches to AI writing instruction. Current AI tools excel at addressing basic linguistic needs but struggle with higher-order writing skills required by advanced learners. Findings emphasise the need for proficiency-responsive AI interventions and enhanced explainability to transform AI assistance into sustainable writing competence.
Copyright (c) 2026 Shaobo Liang , Yingyu Wang , Dan Wu https://creativecommons.org/licenses/by-nc/4.0
Shared agency in information behaviour research: Human–Nonhuman interactions
Introduction. This study examines shared agency in information behaviour, advancing a post-anthropocentric perspective that recognises how humans co-participate with technological, biological, and environmental entities when interacting with information. Method. Using secondary data analysis, the study synthesises findings from four previously published projects employing autoethnography, visual ethnography, mixed methods, and reflective phenomenology. These studies provide empirical insights from contexts including yoga, social media misinformation, and human–companion animal relationships. Analysis. A cross-case thematic analysis was conducted, guided by theoretical frameworks from embodiment, sociomateriality, and multispecies perspective, to examine how agency emerges relationally across different assemblages. Results. Three themes were identified. First, agency is not individually possessed but emerges between entities. Second, it is enacted through material-affective engagements involving bodies and environments. Third, it is grounded in caring connections with others. These findings show that meaning emerges through dynamic interaction rather than isolated individual action. Conclusion. Information behaviour is a relational achievement of shared agency. This reconceptualisation offers insights for ethical and effective human–AI collaborations, encouraging a shift from viewing technologies as tools toward mutual incorporation and participatory sense-making.
Copyright (c) 2026 Niloofar Solhjoo , Jia Tina Du , Yazdan Mansourian https://creativecommons.org/licenses/by-nc/4.0
Dimensions of information search strategies: a study of blind and visually impaired users in mobile digital library environments
Introduction. This study intends to characterize blind and visually impaired (BVI) users’ information search strategies through analysing the dimensions of search tactics and strategies in their interactions with digital libraries (DLs) in the mobile environments. Method. This study recruited 120 BVI participants representing users of four types of mobile devices: iPhone, iPad, Android phone, and Android tablet. Multiple data collection methods were employed to collect data: prequestionnaires, post-system questionnaires, think-aloud protocols, transaction logs, and post-system and post-search interviews. Analysis. Qualitative and descriptive analysis were applied to identify dimensions of information search strategies: intentions, actions, and entities. NVivo was used for qualitative analysis. Additionally, inter-coder reliability for the dimensions was calculated. Results. The initial results of the study identified 13 types of intentions, 14 types of actions, and 15 types of entities. While the intentions encompass cognitive and behavioral goals, the actions focus on access-related activities. The entities range from device/screen readers, DL features/structure, and collections/items. The combination of diverse dimensions constitutes various information search strategies in the mobile DL contexts. Conclusion. The identified intentions, actions, and entities that constitute search strategies can be further mapped to the unique contexts of BVI users, DL systems, and mobile environments.
Copyright (c) 2026 Iris Xie, Wonchan Choi, Hyun Seung Lee, Ning Chiao Wang, Bo Hyun Hong https://creativecommons.org/licenses/by-nc/4.0
Leveraging search engines and LLMs for creative thinking: effects of prompting skills, and domain knowledge
Introduction. We investigated the effects of domain knowledge (DK) and prompting skills by leveraging a traditional search engine and a prompt-based LLM chatbot for a learning-oriented creative task. Method. On a simulated curated calligraphy exhibition task for which one must integrate DK and creativity to write summaries of curatorial planning, we observed behavior when using the NPM Collection, Google Search, and ChatGPT. We assessed the creative thinking demonstrated in the final summaries. User perception of tools supporting creative thinking was evaluated by the creativity support index. Analysis. We analysed information source usage behavior using descriptive statistical analysis and significance testing and used regression analysis to examine the predictive power of tool usage behavior, domain knowledge, and prompting skills for summary writing. Results. We discovered a positive predictive effect of DK and ChatGPT usage on the quality of curatorial planning summaries. Better prompting skills enhanced task performance and perceived creativity. For creative thinking, Google seemed to better foster exploration than ChatGPT. Conclusions. Prompt-based LLM chatbots support learning-oriented creative tasks. As prompting skills are essential, prompting should be integrated into information literacy education. The study provides implications for the design of search systems in human–information retrieval–LLM interaction to better support creative tasks.
Copyright (c) 2026 I-Chin Wu, Hsuan-Yu Lin, Pertti Vakkari https://creativecommons.org/licenses/by-nc/4.0
Daniel Tiger vs. Ms. Rachel: exploring video-based media with babies and toddlers
Introduction. Using video-based media (VBM)—television, movies, YouTube videos, etc—with children under age two remains a debated issue. While child development experts warn against it, some parents continue to use it with their babies and toddlers. This research endeavoured to provide initial insight into the usage of VBM with babies and toddlers, including why and how parents are using it and characteristics of the media being used. Method. Qualitative data from two separate studies were collected through interviews, focus groups, and a daily texting protocol with twenty-two parents of young children, ages 0-30 months. Analysis. A thematic approach was used to analyse the interview, focus group, and texting data. Both inductive and deductive approaches were used in coding the data. Results. The research found that parents are using VBM with their babies and toddlers for a variety of reasons. They are mostly using child-focused media, comprising TV shows, movies, and YouTube videos, with over half of it consisting of low-stimulation media. Conclusion(s). These initial findings provide a foundation and point to the need for more in-depth and expanded research that explores the role and impact of VBM, and particularly low-stimulation media (LSM), in babies’ and toddlers’ daily lives.
Copyright (c) 2026 Kathleen Campana, J. Elizabeth Mills https://creativecommons.org/licenses/by-nc/4.0
Measuring theory through practice: Librarians’ perceptions of relevance, concreteness, and importance
Introduction. This study investigates how reference librarians perceive the relevance, concreteness, and importance of established theories of information behaviour. While the theory–practice gap has been widely discussed, little empirical evidence exists on how practitioners perceive formal theories in relation to their work. Method. We conducted an online survey using plain language descriptions of twelve major theories of information behaviour. Participants rated each theory on three semantic differential scales: irrelevant-relevant to their work, abstract-concrete, and unimportant-important. Analysis. A total of 771 valid questionnaires were analysed using descriptive statistics, correlations, and Wilcoxon signed-rank tests, and were compared with findings from a prior qualitative interview and card-sorting study. Results. Reference librarians evaluated all theories as at least moderately relevant, concrete, and important. Despite strong correlations between relevance and importance ratings, interesting differences emerged: some theories were viewed as more relevant than important, while others were seen as more important than relevant to their work. This suggests that librarians differentiate between immediate applicability and broader conceptual value. Conclusion(s). The study showed that reference librarians make subtle but meaningful distinctions in how they perceive information behaviour theories. A survey using semantic differential scales proved useful in capturing these perceptions and revealed patterns that align with qualitative findings.
Copyright (c) 2026 Tanja Merčun , Amy VanScoy , Africa S. Hands , Katarina Švab https://creativecommons.org/licenses/by-nc/4.0
The impact of parasocial interaction and perceived risk on consumer purchase intention in livestreaming e-commerce
Introduction. Livestreaming e-commerce is a key digital economy driver, yet research lacks a systematic exploration of streamer’s characteristics and communication styles, creating a theoretical gap regarding parasocial interaction and perceived risk. Method. This study takes parasocial interaction and perceived risk as a theoretical framework to construct a dual-path model. The questionnaire survey (N=296) and Structural Equation Modeling (SEM) are employed to examine the mechanism influencing consumer purchase intention in livestreaming e-commerce. Results. The findings revealed three main findings: (1) parasocial interaction positively affects consumer purchase intention, while perceived risk has a reverse effect; (2) streamer’s physical attractiveness and credibility can enhance consumer purchase intention through parasocial interaction, but physical attractiveness increases the perceived risk, and credibility reduces the perceived risk; (3) emotional and cognitive communication can promote consumer purchase intention through parasocial interaction, but the effect on perceived risk is not significant. Conclusion. The study reveals the critical role of streamer initiative in the consumer decision-making process, providing a theoretical basis for optimizing streamer selection, setting up differentiated communication strategies and improving risk regulation. It also expands the application of parasocial interaction and perceived risk theories.
Copyright (c) 2026 Jiaying Li, Shijie Song, Yujun Liu https://creativecommons.org/licenses/by-nc/4.0
Learning from unknown-unknowns: inconsistency-driven sampling for improving LLM entity matching
Introduction. While large language models (LLMs) demonstrate high performance in entity matching, the ‘unknown-unknown’ problem, where models confidently make incorrect predictions, remains a significant challenge. This research focuses on the manifestation of this problem as logical inconsistencies, such as violations of transitivity (e.g., A=B and B=C, but A≠C) across multiple matching decisions. Method. ‘Inconsistent triangles,’ in which the transitive law is violated among three entities, were detected, and scored based on their degree of contradiction. Pairs with higher inconsistency scores were prioritised for annotation, and the resulting labeled data was fed back to the model through fine-tuning or few-shot learning. Analysis. The proposed method was evaluated on multiple datasets, including Japanese and English data. Its performance was compared against existing baseline methods, such as uncertainty sampling and random sampling, using the pairwise F1 score as the primary evaluation metric. Results. The experiments revealed that the proposed inconsistency-driven sampling strategy outperformed or achieved comparable performance to existing methods across all datasets. Conclusion. By leveraging inconsistency to actively select training data, our approach achieves learning efficiency, demonstrating improved entity matching performance under the same annotation budget.
Copyright (c) 2026 Kota Okayama, Hiroyoshi Ito, Atsuyuki Morishima https://creativecommons.org/licenses/by-nc/4.0
Beyond the loop: a research agenda towards a framework for critical AI literacy in the AI-assisted literature review
Introduction. AI tools hold significant promise for enhancing the efficiency and transparency of academic literature reviews by streamlining literature search and data synthesis. However, their uncritical use poses risks to methodological rigor and academic integrity due to algorithmic bias, fabricated information (‘hallucinations’), and opaque AI processes. Current ‘human-in-the-loop’ guidelines often lack clear oversight protocols, potentially fostering intellectual passivity. Method. Through a critical literature review, this paper identifies three paradoxes: the Verification Paradox, where efficiency compromises factual integrity; the Homogenization Paradox, where bias reinforces dominant perspectives, stifling innovation; and the Automation Paradox, where opaque algorithms undermine critical thinking and rigor. Analysis/Results. To address these challenges, we propose a ‘framework for critical AI literacy in IS’, grounded in epistemological agility, methodological transparency, and ethical responsibility. This framework must offer actionable guidance for information systems scholars to responsibly integrate AI into literature reviews, ensuring human expertise and intellectual integrity remain central. Conclusion. By fostering critical engagement with AI tools, this study sets a research agenda for a robust, transparent, and ethically sound research practices in an AI-Assisted research landscape.
Copyright (c) 2026 Dipesh Jalui, Mary Tate, Jocelyn Cranefield https://creativecommons.org/licenses/by-nc/4.0
Occupational identities in the age of generative AI: the case of librarianship
Introduction. This paper analyses AI-generated depictions of librarians to determine their alignment with stereotypical portrayals. Previous research has highlighted gender biases in large language models (LLMs) and AI-generated images. However, no studies have examined AI-generated images of librarians. This study fills that gap by exploring how these images uphold stereotypes. Method. Data was collected from ChatGPT, DALL-E, Midjourney, and Adobe Firefly using gender-neutral prompts in American English and Brazilian Portuguese. Analysis. We performed quantitative and qualitative analysis to compare languages and models. Thematic analysis revealed recurring themes and patterns in the visual representations. Results. Our findings indicate that AI-generated images often depict librarians as white women, with stereotypical elements like glasses and cardigans. We also observed that different model versions and languages generate different portrayals of the profession. When prompted in Brazilian Portuguese, the models tended to offer a more representative image of the professionals. Conclusion. The study underscores the need for a critical approach to Generative AI, as training data reflects societal biases, perpetuating stereotypes. These portrayals can impact the public perception of librarians, potentially alienating users and reinforcing an outdated, predominantly white, female, and middle-class image of the profession.
Copyright (c) 2026 Viviane Ito, Lyric Grimes https://creativecommons.org/licenses/by-nc/4.0
When in need of emotional support, human or AI? An exploratory study on Chinese women's selection mechanism of emotional information sources
Introduction. This study aims to unveil the selection mechanism of information sources among female users for their emotional information needs, exploring the specific role GenAI plays in their existing emotional support network. Method. Adopting a phased qualitative approach of netnography followed by semi-structured interviews, this research collected rich narrative data from 17 Chinese female users. Analysis. The data was analysed using thematic analysis, focusing on three core evaluation dimensions for information source selection: accessibility, interactivity, and the crucial aspect of credibility. Results. The findings reveal that GenAI is regarded as an ‘emotional sanctuary’ to avoid interpersonal risks and satisfy intra-psychic needs. In contrast, while human sources offer deeper emotional resonance and social connection, they are often associated with higher intra-psychic risks. GenAI and human sources play complementary roles. Conclusion(s). The constructed ‘perceived benefits and risks assessment model’ visually elucidates this selection mechanism, providing a new theoretical reference for understanding emerging human-AI emotional interactive relationships.
Copyright (c) 2026 Zhaotong Wu , Yunyi Hu, Hui Yan https://creativecommons.org/licenses/by-nc/4.0
Limitations in cultural context: systematic biases of LLMs in Chinese sentiment analysis
Introduction. Large language models (LLMs) are increasingly applied in Chinese sentiment analysis; however, their ability to interpret sentiment in culturally specific contexts remains uncertain. This study systematically evaluates the potential biases of LLM-based Chinese sentiment analysis, providing an empirical basis for model optimisation and responsible application. Method. A human-AI comparison experiment was conducted at both word and sentence levels. Two hundred Chinese words from four categories and 225 sentences were used as materials. Judgment data on sentiment polarity, intensity, valence, and arousal were collected from native Chinese speakers and representative Chinese and international LLMs. Data analysis was performed using Chi-square tests and Kruskal–Wallis tests. Results. In sentiment polarity judgment, LLMs are highly consistent with humans and outperform the traditional sentiment lexicon. For continuous dimensions (intensity, valence, arousal), LLMs generally show an exaggeration bias, especially for sensory-perceptual words and ironic sentences. The bias stems from the disembodied cognitive nature of models, exaggerated linguistic patterns in training data, and technical characteristics such as the attention mechanism. Conclusion. This study reveals a systematic limitation of LLMs in Chinese sentiment analysis, characterised by accurate classification but exaggerated quantitative evaluations. Consequently, in practical applications, outputs related to sentiment intensity should be interpreted with caution.
Copyright (c) 2026 Ruili Geng , Jiwen Zhang , Ruixian Yang , Mingzhe Quan , Xiang Zheng , Yishuai Xu https://creativecommons.org/licenses/by-nc/4.0
Large language models na ciência da informação: perspectivas técnicas da inteligência artificial aplicadas à organização e à arquitetura da informação(Large language models in information science: perspectives on information organisation and architecture)
Introduction. Despite the popularity of large language models, there are still gaps in understanding how information is organised, represented and structured within these systems. Thus, this study sought to identify and analyse aspects of information science (IS) in LLMs. Method. This is a bibliographic study with a qualitative approach, conducted through a rigorous protocol applied to the ACM digital library, ScienceDirect, Scopus and Web of Science databases. Analysis. A total of 53 studies published between 2022 and 2025 were examined, from which 16 categories of artificial intelligence techniques applied in LLMs were identified. Results. These techniques were related to the four information architecture systems: organisation, labeling, navigation and search, and to classical instruments of information organisation, highlighting the convergence between principles of IS and AI innovations. Conclusions. The articulation between information architecture and information organisation provides conceptual and practical foundations to understand how LLMs structure, represent and make data available. The study points to future research directions, reinforces the relevance of IS in the debate on AI and highlights the role of information professionals in critically mediating between technology and society.
Copyright (c) 2026 Daiane Campos Procópio , Patrícia Nascimento Silva https://creativecommons.org/licenses/by-nc/4.0
An LLM-powered framework for hierarchical topic discovery in LLM research
Introduction. The advancement of large language models (LLMs) has led to a rapidly expanding body of research, making systematic mapping of the research landscape critical for informed policy and resource allocation. We present an LLM-powered framework constructing hierarchical topics to reveal how research emerges and reorganizes. Method. We gather Web of Science (WoS) titles/abstracts, extract topics via GPTopic, and prompt an LLM to form a hierarchy. We integrate quantitative and qualitative analyses, building a bipartite network linking domains and methods. Analysis. The hierarchical topics provide an overview of the LLM research landscape. Trends are derived from monthly aggregations of publications, offering insights into how research topics evolve and shift in the future. Results. AI/ML led overall output, peaking in August 2024, with multimodal learning, systems efficiency, and cybersecurity emerging as key growth engines. Medical LLM research evolved from exploration (2023) to workflow integration (2024), reaching specialized deployment focused on fairness and guidelines by 2025 across medical imaging topics. We successfully forecast two research directions that account for 83.75% of publications in a specific area over the next three months. Conclusion. The framework can effectively generate hierarchical topics for LLM-related research for downstream analysis and can be generalized to other domains.
Copyright (c) 2026 Xuan Lu, Young Soo Ko https://creativecommons.org/licenses/by-nc/4.0
Understanding user experience in generative AI application: Evidence from topic modelling and sentiment analysis of user reviews
Introduction. With the rapid surge of users in generative AI (GenAI) applications, user experience research is moving beyond surveys and experiments toward large-scale analyses of online reviews. Integrating topic and sentiment patterns from these reviews with user experience theory enables a clearer view of users’ concerns and experience gaps. Method. This study analysed Chinese user reviews of DeepSeek using BERTopic for topic modelling combined with sentiment analysis and mapped the findings onto Jesse James Garrett’s five elements of user experience to reveal layered perceptions. Results. Thirty-four topics were identified and grouped into nine categories covering technical stability, device adaptation, AI interaction and functional features. Negative sentiments centred on server instability, system errors and functional deficiencies, whereas positive sentiments highlighted AI performance, emotional support, and distinctive functions. The five-element mapping revealed strategic instability, scope plane functional gaps, structural interaction barriers and framework plane issues with multi-device adaptation. Conclusion(s). Joint topic–sentiment analysis not only uncovers core concerns of GenAI application users but also offers actionable insights for improving technical stability, device adaptation and interaction design, providing a new empirical view for optimising similar applications and advancing user experience research.
Copyright (c) 2026 Chenxin Zhou, Lihong Zhou https://creativecommons.org/licenses/by-nc/4.0
The duality of connectivity: how the connectivity of collaborative networks shapes disruptive innovation
Introduction. This study first reveals the nonlinear impact mechanism of algebraic connectivity in scientific collaboration networks on disruptive innovation, offering a novel perspective for understanding the boundary effects of knowledge flow and the emergence of innovation. Method. Using academic papers in the field of computer science as empirical samples, we first quantify the degree of disruptive innovation in scientific papers using CD-index. Then, we employ the Louvain algorithm to identify the specific weighted collaboration network embedded by scientists and calculate its algebraic connectivity. A two-way fixed effects model is employed, with the quadratic term of algebraic connectivity introduced to test the nonlinear impact mechanism. Results. A significant ‘inverted U-shaped’ relationship is found between the algebraic connectivity of scientific collaboration networks and disruptive innovation, with a inflection point at 0.174. Moderate levels of connectivity facilitate the integration of global knowledge, thereby promoting disruptive innovation. Both excessively high and low levels of connectivity suppress breakthroughs in disruptive innovation. Moderating effect reveals that higher knowledge density accelerates the marginal benefits of connectivity, allowing the network to form an innovation advantage at relatively low connectivity levels. Conclusion. The emergence of disruptive innovation requires an emphasis on seeking structural balance between knowledge integration and cognitive diversity.
Copyright (c) 2026 Yingqun Li, Chuhui Zhang, Zhiwei Hu, Lei Pei https://creativecommons.org/licenses/by-nc/4.0
UC-TAM: an unsupervised model for fine-grained semantic association construction across large-scale power system standards documents
Introduction. Power system standards constitute a vast, complex repository, yet existing methods struggle with fine-grained semantic association (e.g., clause-level) due to coarse-grained analysis and reliance on manual annotation. This study develops an unsupervised, domain-adapted approach to address this gap. Method. We propose UC-TAM, which integrates a 134,945-term power lexicon with a hierarchical attention framework and unsupervised clustering. Clauses serve as atomic semantic units, where intra- and cross-document relations are captured through multi-head attention and embedded in a shared space, followed by K-means clustering for semantic association discovery. Analysis. Comparative experiments against a Sentence-BERT + K-means baseline were conducted on subsets of standards, evaluated with Silhouette (SC), Calinski–Harabasz (CH), and Davies–Bouldin (DB) indices. Results. UC-TAM outperformed the baseline with improvements of 27.7% (SC), 31.3% (CH), and 19.6% (DB). A case study confirmed practical utility, with expert-rated clustering accuracy of 88% versus 75% for the baseline. Performance improved consistently with dataset size, demonstrating scalability and robustness. Conclusion. UC-TAM highlights both the feasibility and the practical value of unsupervised, domain-aware approaches to standard document analysis, offering a pathway toward more intelligent, automated, and fine-grained management of standards.
Copyright (c) 2026 Weiwei Zheng , Lu Wang , Xiaoqun Yuan , Yanrong Zheng , Wei Xie , Yanan Liu , Liang Zhao https://creativecommons.org/licenses/by-nc/4.0
From framework to flexibility: a heuristic scheme for institutional & individual interpretation and application of digital competencies
Introduction. This paper introduces a tiered digital literacy taxonomy that reimagines how digital competencies are interpreted and applied across institutional and individual contexts. Moving beyond static frameworks, we propose a heuristic model that captures the dynamic, co-constructed nature of digital literacy. Method. Drawing on real-world examples from Scotland, the UK, and global initiatives, we employed explanatory examples to illustrate how players dynamically construct what constitutes digital literacy in context. Analysis. We demonstrate how institutional frameworks often diverge from lived practices, and how users reinterpret competencies like communication, safety, and problem-solving in context-specific ways. Institutional characterisations (for example, the EU DigComp Digital Competences, the UK’s Essential Digital Skills framework, and UNESCO’s global literacy framework) set the tone, while everyday practices (for example, those in the Scottish public sector or digital inclusion initiatives) reinterpret or extend them. Results. Our taxonomy highlights the interpretive flexibility of digital skills and introduces an effort-versus-impact matrix to guide strategic prioritisation in resource-constrained environments. Conclusion. Ultimately, we argue for a participatory, adaptive approach to digital literacy, allowing taxonomies to develop in response to users rather than focusing on fixed checklists.
Copyright (c) 2026 Collins Ovie, Pritam Chita, David Brazier, David Haynes, Peter Cruickshank https://creativecommons.org/licenses/by-nc/4.0
Breaking the mold of knowledge imposition: reconstruct the digital literacy education model in academic libraries under the Scottish enlightenment
Introduction. This paper examines a new model of digital literacy education (DLE) in academic libraries. How Scottish Enlightenment ideas provide philosophical reflection and reference for DLE in contemporary academic libraries and break through the traditional knowledge imposition model. Method. Drawing on Adam Smith’s theory of moral sentiments, David Hume’s theory of habit, and Adam Ferguson’s theory of spontaneous order, the study explores a new model of DLE consisting of three elements: space, resources, and librarians. Analysis. The model covers how to build the real and virtual digital literacy space, how to develop resources to strengthen students’ learning subjectivity, and how librarians need to change traditional teaching methods. Results. Academic libraries need to create digital literacy learning situation that integrates physics and virtual, develop structured digital literacy training courses, interactive self-learning tools, open education resources, practical digital literacy programs, and other resources. Librarian should become guider, maintainers of order, and evaluators of educational effectiveness. Conclusions. Academic libraries should integrate educational and psychological theories, consolidate the philosophical foundation of DLE, and reconstruct the construction, integration, and presentation of resources with students as the center
Copyright (c) 2026 ZhenJia Fan, YiMei He https://creativecommons.org/licenses/by-nc/4.0
Reframing creative learning: a conceptual framework for design literacy in the GenAI era
Introduction. Generative artificial intelligence (GenAI) is reshaping how creative learning engages with information. GenAI systems extend access and accelerate ideation, yet they also introduce epistemic unreliability, diminished originality, and ethical ambiguity. This research examines how design learning across formal, non-formal, and informal settings are destabilised by GenAI’s mediation of information and argues for a framework to sustain design literacy in the GenAI era. Method. This study employs a conceptual framework–building approach, drawing on information science, AI literacy, and design pedagogy to articulate four planes of competency: epistemic, operational, ethical–legal, and reflective. It is developed through integrative literature review and abductive synthesis, clustering concepts across disciplines. Analysis. Within these planes, nine action components are identified: provenance tracing, uncertainty tagging, cross-modal triangulation, plausibility checks, prompt engineering, iterative prototyping with AI, bias and harm review, authorship disclosure, and reflective critique. Their application is illustrated through scenarios across contexts varying formality. Results. The framework shows how these competencies preserve curiosity, iteration, and originality while mitigating misinformation, bias, and overreliance on GenAI. Conclusion(s). This study proposes a conceptual framework for GenAI-impacted creative learning, reframes design literacy as information practice, and outlines a research agenda for empirical validation in curricula, cultural programs, and informal learning.
Copyright (c) 2026 Asif H Zeshan, Xiao Hu https://creativecommons.org/licenses/by-nc/4.0
Beyond or within the binary? Constructing gendered meanings in generative AI use
Introduction. GenAI is increasingly embedded in daily life, yet its ostensibly neutral design often becomes a site for gendered interpretations. This study examines how Gen Z users in China perceive and construct gendered traits in GenAI, situating their accounts within broader concerns of neutrality and equity in information society. Method. Semi-structured interviews were conducted with 12 participants who regularly use multiple GenAI platforms. Discussions explored textual, visual, and auditory cues, user projections, and contextual triggers. Analysis. Thematic analysis, informed by Butler’s theory of performativity and Haraway’s cyborg imaginary, was applied to 73,480 words of transcripts. Coding identified patterns in participants’ accounts of gendered cues, user projection, contextual attribution, and reflections on neutrality. Results. Participants consistently mapped rational, didactic tones onto masculine authority and empathetic language onto feminine care. Avatars and voices anchored gender perceptions, while mimicry highlighted both adaptability and artificiality. Attribution also drew on cultural repertoires, personal experiences, and task contexts. Conclusion. Neutrality in GenAI does not erase gender but becomes a site of projection and negotiation. The findings show how such systems can reproduce stereotypes while also enabling more inclusive, post-binary imaginaries, underscoring the need for critical AI literacy and designs that advance information equity.
Copyright (c) 2026 Zhiyuan Lai, Yunjie Tang https://creativecommons.org/licenses/by-nc/4.0
Artificial intelligence in libraries: a systematic review of upskilling, challenges, and future research directions
Introduction. Libraries, as trusted institutions, are positioned to advance AI literacy for both staff and patrons. This study investigates how AI literacy has been conceptualised and implemented in libraries and examines the challenges these institutions face in AI upskilling and integrating AI into their services. Method. A systematic literature review using PRISMA guidelines to identify peer-reviewed articles and practitioner reports on AI upskilling in libraries. Analysis. Fourteen articles published between 2021 and 2025 were examined, spanning academic, public, and school libraries. Both thematic and comparative analysis were used to synthesise findings. Results. Findings reveal significant variation in definitions of AI literacy, sectoral differences in focus (staff training in academic libraries, patron programs in public libraries, early digital citizenship in schools), and recurring challenges including cost, vendor dependence, staff anxieties, and lack of outcome evaluation. Geographic patterns show Asia leading in empirical studies, while Western literature is largely conceptual. Conclusion. To remain relevant, libraries must move beyond fragmented, vendor-driven initiatives toward clearer definitions, equity-centered approaches, and scalable, evidence-based models that empower both staff and patrons in an AI-driven era.
Copyright (c) 2026 Erezi Ogbo-Gebhardt , Agnes G. Pearcy , Joseph B. Wiggins , Yerika Jimenez https://creativecommons.org/licenses/by-nc/4.0
Research topic mining and evolution analysis of digital literacy within higher education based on BERTopic
Introduction. Digital literacy is becoming increasingly central to higher education in the context of rapid digitalisation and the adoption of AI. Accordingly, it is necessary to analyse the research topics and evolutionary trends of digital literacy in higher education. Method. This study applies BERTopic to analyse 2,605 bibliographic records from the Web of Science Core Collection, using SBERT embeddings, MDS reduction, K-means clustering, and LLR weighting. Results. Seven key topics were identified, including Teacher digital literacy and professional training, social media, mental health, and digital inequality, digital transformation in nursing and medical education, Artificial intelligence and educational innovation, digital health literacy, Student digital citizenship and information literacy, and digital learning environments and student outcomes. Temporal analysis across five periods (1997–2025) reveals how digital health and AI research surged during the pandemic, while responsible digital practices gained prominence in recent years. Conclusions. The findings map the field’s evolving knowledge structure and provide evidence-based insights for policymakers and educators to inform the design of curriculum, instructional reform, and digital competence development.
Copyright (c) 2026 Shuangling Cheng, Shubin Zhou https://creativecommons.org/licenses/by-nc/4.0
Seeking the mission and opportunities for LIS in the AI era: a systematic review of empirical research on teenagers' artificial intelligence literacy (TAIL)
Introduction. We conducted a systematic review of empirical research on Teenagers' AI literacy (TAIL), aiming to explore opportunities and future research directions for the LIS field in TAIL studies. Method. We conducted this study using the four-element framework of systematic review. After two rounds of screening, a total of 41 articles were ultimately included in this study. Analysis. We conducted a coded analysis of the included articles based on the RQs. Results. We identified 3 categories of research topics: TAIL education/cultivation, scale development, and relationship exploration. We also summarised 3 research patterns: Design-Implementation-Validation pattern, Investigation-Exploration pattern, and Hypothesis-Verification pattern. Conclusion(s). We found that despite existing AI literacy practices for teenagers in the LIS field, current research with distinct LIS characteristics remains scarce. Future efforts should clarify the responsibilities and role of LIS in TAIL research and practice, leveraging its resource advantages, practical field strengths, and information perspective. Furthermore, this study outlines future research directions based on these three strengths.
Copyright (c) 2026 Jing Liu , Jiajing Ma, Guoye Sun , Shu Fan https://creativecommons.org/licenses/by-nc/4.0
Illuminating connections and contexts: building an ontology for Chinese ration coupon archival resources based on RiC-O
Introduction. Ration coupons defined everyday life in China from 1953 to 1993, and evolving trends in research demand more sophisticated ways of describing archival resources that document this unique period of history. This study constructed the Chinese Ration Coupon Ontology (CRC-O) using the Records in Contexts-Ontology (RiC-O) model to represent and describe a resource collection of ration coupons, policy documents, and oral histories. Method. CRC-O was built through combining a bottom-up process of inductively identifying key metadata elements through analysing the resources with a top-down application of RiC-O via mapping processes and creating local extensions. Results. CRC-O provides a unified conceptual framework that links three types of resources through shared entities. It reuses 24 core classes and over 50 object and data properties from RiC-O and introduces local extensions. The construction process also illuminated the strengths and limitations of RiC-O. Conclusion. The study offers an application of RiC-O to a new domain, demonstrating its capability to represent and integrate multiple types of archival resources, surface connections between resources, and enable rich, detailed descriptions.
Copyright (c) 2026 Linqing Ma , Ruohua Han , Xiaoyan Yang Yang , Yina Wu , Jiaqi Shi https://creativecommons.org/licenses/by-nc/4.0
Exploring immersive cultural heritage experiences: a user study of a VR application featuring ancient manuscripts
Introduction. This study aims to explore how general users interact with and perceive cultural heritage through VR applications that feature ancient manuscripts. Specifically, it examines how VR experiences influence users’ interests, knowledge acquisition, and engagement with cultural heritage, focusing on the effects of multiple information channels, plot structure, and VR device interactions. Method. This study employs a mix-method user study design in which 37 participants were asked to explore the VR application featuring the Qing Dynasty manuscript, ‘Nan Huairen Ti Ben’. Data was collected through pre-task and post-task questionnaires, VR screen recordings, and interaction maps created by the participants. Analysis. We conducted thematic analysis on the qualitative data and complemented with descriptive and inferential statistical analyses of quantitative data. Results. The VR application effectively piques users’ interest in the cultural heritage, including its historical and social context, and current state. Key design suggestions include integrating narration with other information channels, allowing for a balance of guided and exploratory interactions, and optimizing device interfaces for cultural heritage contexts. The study also proposes a design framework applicable to the broader VR cultural heritage field. Conclusion(s). This study proposes a design framework and suggestions for VR cultural heritage, highlighting user needs, information channels, plot structure, and device interactions.
Copyright (c) 2026 Wenqi Li, Zeyang Luo, Pengyi Zhang https://creativecommons.org/licenses/by-nc/4.0
Engineering oral stories: a conceptual model of traditions as water
Introduction. Oral narratives often change form and ownership as they transition from speech to text, yet cataloguing practices rarely capture this fluidity. This study examines how description can mirror the layered nature of stories, rather than freezing them at the moment of initial recording. Method. A comparative case design is used. First, recensions of the Táin Bó Cúailnge are examined through de Laet and Mol’s (2000) ‘fluid‑technology’ lens to model how narrative parts are exchanged like pump components. Second, Mapping Assiniboia Residential School Survivor Stories: Did You See Us? is presented to demonstrate an Indigenous perspective in contemporary North America. Analysis. The analysis of these two case studies is a literary review that provides a theoretical framing of scholarly responses to FRBR, addressing and situating how different oral traditions align in a central ambiguity. Results. In both cases, a recurring chain appeared: community blueprint, local knowledge carriers, and distribution principles. Conventional catalogues only document the carrier, leaving the blueprint and flow unseen. A three-tier FRBR-Lite model captures all layers without the data overhead that hinders full FRBR adoption. Conclusions. Treating description as hydraulic stewardship—tracking blueprint, pump, and flow—aligns metadata with long-standing narrative fluidity and honours Indigenous sovereignty by incorporating community protocols at the carrier level.
Copyright (c) 2026 Andrew Wiebe https://creativecommons.org/licenses/by-nc/4.0
‘Appears to be about’: an evaluation of AI-generated metadata quality for community archives
Introduction. We report on an evaluation of the quality of metadata generated by a general purpose chatbot using items from a community organisation archive. Method. We developed an evaluation framework adapting quality dimensions from prior work and applied it to analyse a sample of 140 Dublin Core metadata records created by ChatGPT 4o from primary sources drawn from a community organisation collection, based on informal prompts. Analysis. Using independent qualitative coders and a peer review process, we assessed accuracy, conformance, consistency, completeness, objectiveness, transparency, bias, engagement, meaning and context, understandability, and provenance. Results. We found approximately 70% of elements to be accurate. Most records were substantially complete and objective but often vague. Records exhibited significant inconsistencies in how ChatGPT completed fields, conformed to the Dublin Core schema, and interpreted primary sources. Conclusion(s). General purpose AI chatbots have the capacity to provide substantial ‘rough draft’ descriptive records for community collections, even with minimal prompting. These records require significant human intervention to ensure quality in terms of completeness, conformance to schema, accuracy, and meaningfulness to users. We offer insights for organisations and communities working with AI chatbots for description, along with implications for broader archival practice.
Copyright (c) 2026 Nikki Wise, Katrina Fenlon, Diana Marsh, Amanda Sorensen, Ugoma Smoke, Candy Navarette, Lucy Havens https://creativecommons.org/licenses/by-nc/4.0
‘Metadata is wonderful, but there’s a coldness to it’: exploring the visual accessibility of cultural heritage through participatory design
Introduction. Ensuring access to digital visual cultural heritage (VCH) for people who are blind or low vision (BLV) requires dedicated effort. Many digitised collections lack alt text, transcriptions, or descriptions that would enable independent access. Method. We conducted participatory design sessions with BLV participants, cultural heritage experts, and stakeholders at the Library of Congress (LOC) to explore how access to VCH collections might be improved. Mixed groups of BLV and sighted participants completed three activities: 1) identifying categories of information valued in image descriptions, 2) evaluating descriptive sources through a Wizard-of-Oz method, and 3) brainstorming to envision future systems. Analysis. We analysed category rankings from Activity 1, evaluations of descriptive sources from Activity 2, and qualitatively examined insights from one study session of Activity 3. Results. Participants emphasised the importance of descriptions that extend beyond metadata, including vivid visual details, human presence, and contextual information. Human-provided descriptions were most valued, AI-generated descriptions showed potential but required oversight, and metadata-based descriptions were seen as accurate yet insufficient. Conclusion. Our findings underscore the need for layered descriptive strategies combining factual precision with interpretive richness, ensuring equitable access for blind users.
Copyright (c) 2026 Victoria Van Hyning , Pramod Chundury https://creativecommons.org/licenses/by-nc/4.0
Wasteback Machine: a method for quantitative measurement of the archived web
Introduction. Web archives are traditionally viewed as repositories of cultural memory, yet they have been theorised as computational sources for quantitative, longitudinal analysis of the web. This paper examines their potential for mapping the structural and environmental impacts of web pages, demonstrating broader applicability for web analytics research. Method. We introduce Wasteback Machine, an open-source, extensible framework that operationalises the analytical potential of web archives. It enables reproducible, scalable measurement of page size and composition through programmatic access, structured resource extraction and mechanisms to mitigate distortions introduced during archiving and replay. Analysis. The method is demonstrated through a case study of the United Nations Climate Change (UNFCCC) homepage, performing longitudinal analyses to capture temporal dynamics in size and compositional evolution. By situating web content within socio-technical and infrastructural contexts, the approach allows consistent comparison over time while accounting for archival limitations. Results. Findings reveal trends in page growth, complexity and cumulative digital resource use. Despite their fragmentary nature, web archives provide sufficient fidelity to reconstruct historical practices and estimate relative environmental impacts. Conclusion. Wasteback Machine demonstrates that web archives function as computational infrastructures, enabling rigorous, evidence-based investigation of web evolution and the environmental footprint of digital content.
Copyright (c) 2026 David Mahoney https://creativecommons.org/licenses/by-nc/4.0
Assessing digital preservation training needs in cultural heritage institutions in Saudi Arabia
Introduction. We discuss an investigation into the digital preservation training needs of Saudi Arabia’s cultural heritage institutions, where digital preservation is in its infancy. Assessing training needs is vital to provide programmes tailored to digital preservation specialists’ distinctive needs. Method. An exploratory qualitative case study design was chosen, involving selected managers and practitioners from relevant Saudi cultural heritage institutions. In this paper we report on the online survey with King Abdulaziz Foundation for Research and Archives (Darah), King Abdul Aziz Public Library, King Fahad National Library, Saudi National Centre for Archives and Records, Makkah Centre for Archives and Records, King Abdullah University Library. Analysis. Data from 37 survey respondents were analysed using the statistical package SPSS and Braun and Clarke’s six steps for thematic analysis; NVivo software was used to assist with coding and themes development. Results. Findings help fill a regional gap in a predominantly Western-centric literature on digital preservation training and offer insights for cultural heritage information management and international digital humanities research. Conclusion. To safeguard long term preservation of cultural heritage, training needs of digital preservation specialists in Saudi Arabia and beyond must be adequately addressed, planned for, financially and institutionally supported, adequately communicated, and promoted.
Copyright (c) 2026 Ghaliah Albushra , Perla Innocenti https://creativecommons.org/licenses/by-nc/4.0
Archives search as a complex sensemaking task
Introduction. This study investigated scholar’s behavior in archival institutions to develop more effective search tools for searching paper-based materials in archival institutions. Method. The scholar worked in the U.S. National Archives and was asked to keep a detailed diary of their actions and decisions. The principal analysis was conducted based on this diary. Analysis. In an open coding process, the parts of the diary relevant to our research were identified and assigned an initial code. These codes were refined by repeating the process twice, merging and splitting codes as necessary. Results. Six codes - ‘Set a Goal’, ‘Choose a Strategy’, ‘Prioritising’, ‘Select Boxes’, ‘Examine Documents’ and ‘update mental model’ - were identified. These represent an iterative, hierarchically structured sensemaking process in which changes to plans were based not only on what was found, but also on what was learned about what existed to be found. Conclusion(s). This study shows an example of how complex actions and decisions occur when searching physical materials. It could help in understanding what kinds of tools could be developed to support such activities.
Copyright (c) 2026 Emi Ishita , Tokinori Suzuki , Douglas W. Oard , Yoichi Tomiura https://creativecommons.org/licenses/by-nc/4.0
Perceptions of an immersive learning experience: what do reviews of an architecture cruise reveal?
Introduction. Immersive experiences in cultural heritage environments often involve leisure learning. We studied online reviews of an architecture cruise to explore what is communicated about the experience. Method. Two hundred Tripadvisor cruise reviews were collected. After initial screening, 199 reviews were retained and coded by the research team for mentions about the experience and learning. Analysis. Using both deductive and inductive coding within a storytelling framework, People (those involved in the experience), Places (including buildings and history), and Perceptions (reviewers’ affective responses) in reviews were coded. References to learning or to specific knowledge gained were also coded. Results. People were the most reported storytelling-related category, with docents praised for their knowledge, communication style, and passion. Perceptions reflected strong emotional connections of participants. Places focused on Chicago’s architecture and history, appreciated through the city’s visual impact. Although only one-third of reviews mentioned learning, the experiential elements related to storytelling were central to how tourists expressed meaningful connections with leisure learning in cultural heritage settings. Conclusion. Storytelling emerges as a useful lens for understanding leisure learning in cultural heritage tourism. Analysing online reviews helps identify which aspects of immersive experiences resonate with visitors and where enhancements may support more meaningful reflections.
Copyright (c) 2026 Heather Moulaison-Sandy, Danielle Oprean, Wilson Castano https://creativecommons.org/licenses/by-nc/4.0
International public cultural digitalisation: Technology, space, and service
Introduction. How to provide intelligent and efficient cultural public services is a global issue. Based on the conceptualisation of 'public cultural digitalisation', this study aims to conduct a review of international cutting-edge research on public cultural digitalisation and anticipate future research directions. Method. Under the guidance of experts specialising in public culture, a comprehensive retrieving, retrospecting, screening, data extraction and result analysis of relevant literature regarding the key issues of public cultural digitalisation were conducted, 84 core papers selected for analysis. Analysis. Three researchers extracted the core information elements of the selected literature based on the coding scheme, and thematic analysis method was used to conduct text coding on Nvivo. Results. A knowledge framework of the international public cultural digitalisation with themes of 'technology', 'space' and 'service' is conducted, potential systemic risks that public cultural digitalisation may encounter identified. Conclusion. An integrated knowledge framework for public cultural digitalisation constructed in this study can serve as an interpretive tool in user-oriented, multi-party coordinated, and local-oriented application scenarios.
Copyright (c) 2026 Tongshu Wu , Tingting Zhuo , Qingqing Ye , Yi Chen https://creativecommons.org/licenses/by-nc/4.0
Defining the ‘good’ in educational TikTok videos: Authenticity, literacies, and digital enlightenment
Introduction. This study examines what makes an educational TikTok video ‘good’ from the perspective of learners who actively use the platform. While prior work highlights design principles and instructional strategies, little research investigates how learners themselves define effectiveness in short-form digital video. Method. Using grounded theory, the team conducted semi-structured Zoom interviews with 27 TikTok users who had learned something new on the platform within the past two years. Participants, recruited through snowball sampling, represented diverse demographics and topical interests. Interviews were transcribed and analyzed through open, axial, and selective coding. Analysis. Six interdependent domains shaped participants’ evaluations: Content and Engagement, Delivery and Pedagogy, Affective Qualities, Social and Community, Credibility and Trust, and Platform Affordances. Results. Participants defined good educational videos as those that integrate clarity, authenticity, community interaction, and intentional use of TikTok’s features. Videos stand out when they balance entertainment with pedagogy, build trust through authentic delivery, and act as gateways to deeper exploration. Conclusion. The study offers a sociotechnical framework that bridges cognitive, affective, social, and technological dimensions of learning, presenting implications for educators, librarians, and creators designing effective video-based instruction.
Copyright (c) 2026 Joe Sánchez, Kayla Booth, Isabel Karolczak https://creativecommons.org/licenses/by-nc/4.0
Who do we need to invite to the parlor? Curriculum deliberations and assessment approaches in conversation with course readings
Introduction. This research examines major themes in an MLIS curriculum through an analysis of program course readings in response to the 2023 revision of the ALA Core Competencies. Method. Course readings were gathered for all courses in an MLIS curriculum. 3,406 readings were collected, including webpages, journal articles, conference papers, book chapters, and books. Analysis. The visualisation of the bibliographic network was created using titles, keywords, and abstracts of the readings. Textual analysis of the full text of the course readings was conducted utilising topic modelling analysis. Quantifiable bibliographic information was analysed using basic descriptive statistics. Results. Both bibliographic and topic model analyses indicated various nuanced DEI-related themes were present throughout the course readings, including topics related to race, gender, power, privacy, ethics, and legal considerations. Additionally, the analysis indicated strong breadth and depth within the curriculum. Conclusion(s). Topic modelling and visualisation of assigned course readings render the LIS ‘parlor’ as a network of conversations that we can utilise to assess and guide the curriculum in evolving and aligning with professional competencies.
Copyright (c) 2026 Angela P. Murillo, Andrea Copeland, Charles Sutton, Jenn Sheridan, Cherry Gupta https://creativecommons.org/licenses/by-nc/4.0
One degree, two disciplines? Examining the presence of archival concepts in American library association accredited core courses
Introduction. A master’s degree from a program accredited by the American Library Association has become the preferred credential for American archivists. Archival studies students graduate knowing library core competencies. But is the inverse true? This preliminary study examines the presence of archival concepts within core courses of ALA accredited programs in the USA. Method. Using ALA’s database of accredited programs, we identified the core courses for each program. We then searched for syllabi. If no syllabi were available, we analysed course descriptions, learning outcomes, and ALA accreditation self-study reports regarding core courses. This resulted in a data pool of 53 programs. Analysis. Using an iterative approach, we analysed the data and created rating categories to indicate depth of presence of archival studies in core courses. Once the categories were established, we coded the data. Results. Our qualitative analysis of the data reveals that archival studies topics are present in the core curriculum of 20 out of 53 programs analysed. However, the extent of this presence varies. Conclusions. Archival concepts are being taught in ALA accredited master’s programs, but there is room for growth in order to facilitate collaboration between archivists and librarians and promote better understanding of each other’s disciplines.
Copyright (c) 2026 Caitlin Christian-Lamb , Ana Roeschley https://creativecommons.org/licenses/by-nc/4.0
Preparing library and information studies students for an AI-driven future: student perceptions and curriculum insights from the iSchool at University College Dublin (UCD), Ireland
Introduction. This paper reports on a study of MLIS (Master of Library and Information Studies) and Graduate Diploma LIS students at UCD’s iSchool, examining their perceptions of AI’s impact on the LIS workplace, its influence on their professional competence and preparedness for roles requiring AI knowledge and skills, and the AI-related content they deem essential for the curriculum. Method. An anonymous online survey was conducted targeting MLIS and Graduate Diploma LIS students at UCD’s iSchool in Dublin, Ireland. Analysis. A mixed-methods analysis of the survey data was used. Quantitative responses were analysed using SurveyMonkey's reporting features, while qualitative responses to two open-ended questions were coded thematically in Microsoft Excel. Results. The results reveal students’ ambivalence and ethical concerns about AI’s impact on their profession, alongside interest in developing AI competencies. They recognise efficiency benefits but emphasise human-centred services and call for integrating ethics, privacy, and AI literacy into the curriculum to prepare for evolving roles. Conclusion. AI offers efficiency and workflow improvements for LIS, but students’ ethical concerns highlight the need for curricula that combine technical engagement with critical reflection to prepare graduates for responsible use.
Copyright (c) 2026 Stefanie Havelka, Claire McGuinness https://creativecommons.org/licenses/by-nc/4.0
Bring back the blue book? A reflection on teaching strategies, engaged pedagogy, and the challenges of GenAI in the classroom
Introduction. This paper reflects on teaching practices implemented as a pre-doctoral lecturer in undergraduate informatics courses on race, gender, information, and technology. It reintroduces the blue book not as a punitive measure against generative AI (GenAI), but as an intentional analogue practice to foster engagement, creativity, and reflection in the classroom. Approach. Through literature review, applied practice, and framed by feminist, decolonial, and critical information studies, the paper discusses inclusive strategies such as in-class journaling, student-led facilitation, and multimodal final projects that encourage diverse learning styles and redistribute power in classroom dynamics. The reflection emphasises the importance of diversifying reading lists, valuing lived experience, and offering students meaningful choice in demonstrating their learning. These approaches respond to the lingering effects of the COVID-19 pandemic on student attention and participation, while also addressing the challenges and risks posed by the rise and prevalence of GenAI in higher education. There is also an acknowledgement of limitations and need for future work. Conclusion. Ultimately, this paper argues for a pedagogy of engagement that resists both nostalgia and technological determinism, foregrounding human experience, care, and community as essential elements of learning in a rapidly changing educational environment.
Copyright (c) 2026 Yvette Iribe Ramirez https://creativecommons.org/licenses/by-nc/4.0
Desarrollo de un marco curricular común para potenciar habilidades de investigación e información en la educación superior mexicana.
Introducción: Se aborda el desafío de la enseñanza de habilidades de investigación en la educación superior, especialmente en el contexto mexicano. Ante el reto de enseñar materias de investigación, el objetivo fue diseñar un Marco Curricular Común (MCC) a partir del análisis de las mejores prácticas internacionales para potenciar la formación en investigación. Método: Se realizó un análisis de contenido cualitativo de 50 sílabos de licenciatura de 17 países. La muestra se seleccionó de instituciones de alto rango según los SCImago, considerando accesibilidad e idioma (inglés, español y portugués). Los datos se analizaron mediante una lista de verificación con seis dimensiones, incluyendo competencias, contenidos y alfabetización informacional (ALFIN), para identificar fortalezas y debilidades. Resultados: Los hallazgos revelan una disparidad. Aunque la mayoría de los sílabos describen adecuadamente los pasos procedimentales de la investigación, fallan en integrar tecnologías modernas y enseñar explícitamente habilidades de ALFIN. Adicionalmente, las bibliografías de los cursos resultaron estar, en su mayoría, desactualizadas y con poca diversidad. Conclusión: Se concluye que es necesario un marco que integre el proceso investigativo con las alfabetizaciones informacional y digital. El MCC propuesto surge como un modelo para subsanar estas deficiencias y elevar la calidad de la educación en investigación.
Copyright (c) 2026 Alejandro Villegas-Muro , Juan D. Machin-Mastromatteo https://creativecommons.org/licenses/by-nc/4.0
Perfis profissionais dos mestres em ciência da informação da Universidade do Porto
Introdução. O reconhecimento da importância do acompanhamento do percurso profissional dos alumni tem vindo a crescer. No entanto, métodos tradicionais de recolha de informação, como os inquéritos, apresentam limitações. Neste contexto, o LinkedIn surge como fonte complementar para o estudo dos percursos profissionais dos diplomados. Método. Foram pesquisados, extraídos, normalizados e analisados perfis de LinkedIn dos diplomados até ao ano de 2023 do Mestrado em Ciência da Informação (MCI) e do seu antecessor, o Mestrado em Gestão da Informação (MGI). Análise. Procedeu-se à análise das características dos diplomados e dos respetivos percursos profissionais, incidindo sobre os cargos desempenhados (designações completas e termos individuais), o número e a duração das experiências profissionais e o perfil dos empregadores. Resultados. Os diplomados do MCI referem, sobretudo, cargos de consultor e gestor de informação, e possuem percursos de maior mobilidade. Os do MGI exercem principalmente funções de docência, investigação e gestão, com percursos mais estáveis e empregadores maioritariamente do setor do ensino superior. Conclusão. O estudo contribui para a clarificação dos percursos profissionais em ciência da informação e demonstra o potencial do LinkedIn como fonte complementar para o acompanhamento dos alumni.
Copyright (c) 2026 Inês Aparício , Carla Teixeira Lopes https://creativecommons.org/licenses/by-nc/4.0
Navigating the generative frontier: adoption, challenges, and strategic realignment of GAI in the Chinese publishing industry
Introduction. Generative artificial intelligence (GAI) is reshaping knowledge-intensive sectors, yet empirical research on its organizational adoption within non-Western contexts remains scarce. This study investigates GAI integration in the Chinese publishing industry using the technology-organization-environment (TOE) framework. Method. A mixed-methods approach was employed, involving 44 semi-structured interviews with senior managers from specialized, university, and comprehensive publishers, alongside digital culture groups. Data collection occurred between April and October 2024. Analysis. Qualitative data underwent hybrid thematic analysis to generate a codebook. These data were then quantised into a binary matrix, and statistical methods, including one-way ANOVA, were used to examine relationships and variations across publisher types. Results. Findings reveal cautious optimism constrained by tool immaturity and copyright ambiguity. A strategic divergence emerged: specialized and university presses prioritize accuracy amidst resource constraints, while digital groups leverage investments to reshape the ecosystem. Conclusion(s). The industry faces a tension between efficiency goals and structural barriers like the ‘versatile talent’ gap and legal uncertainty. Future strategy depends on evolving from content production to intelligent data provision.
Copyright (c) 2026 Chen He, Qian Xiao, Jie Xu, Jiayun Wang https://creativecommons.org/licenses/by-nc/4.0
Can digital transformation enable distressed manufacturing SMEs turnaround? The mediating role of supply chain resilience
Introduction. This study examines how digital transformation affects the turnaround performance of manufacturing small and medium-sized enterprises (SMEs) under financial distress. While digital transformation is widely regarded as a critical driver of competitiveness, its role in the recovery of distressed firms remains insufficiently understood. Method. We draw on data from financially distressed manufacturing SMEs and develop an empirical framework to assess the relationship between digital transformation, supply chain resilience, and turnaround performance. Analysis. A quantitative analysis was conducted on a dataset comprising 436 manufacturing SMEs in financial distress. Using Stata, we tested the nonlinear effects of digital transformation and examined the mediating role of supply chain resilience. Results. The findings reveal an inverted U-shaped relationship between digital transformation and turnaround performance. Specifically, moderate levels of digital transformation enhance supply chain resilience, which in turn facilitates effective turnaround, whereas excessive transformation reduces resilience and impedes recovery. Conclusion(s). This study contributes to digital transformation and crisis management research by demonstrating its dual impact on SMEs’ turnaround. It identifies supply chain resilience as the key mechanism linking digital transformation to recovery and offers insights for managers to balance digital investment with organisational adaptability.
Copyright (c) 2026 Feifei Yu , Peijuan Zhu , Yuwei Yang , Chao Lu https://creativecommons.org/licenses/by-nc/4.0
Creating digital information with algorithms and artificial intelligence
Introduction. This paper discusses the use of digital information for content creation, reviews different techniques of AI that are used to create digital information, and presents examples of algorithms that are used to create digital content. Further, the paper discusses how information created by AI is becoming essential in developing the emerging digital society. Method. This paper is focused on concepts relating to the use of AI to create digital content and digital information. The method used is a review of current AI techniques used to create digital content including algorithms and other techniques of AI. Analysis. As a concept paper, the focus is to provide a critical discussion of AI and algorithms with the goal to create digital information and content. The basics of creating digital information are presented as is a brief review of current machine learning algorithms. Results. The discussion presented in the paper highlights the increasing use of algorithms in society and that issues associated with information science and ethics are impacted by the use of AI. Conclusions. The paper concludes with a discussion of future directions in the use of AI-generated information for smarter and more agentic computing systems.
Copyright (c) 2026 Jessica Barfield https://creativecommons.org/licenses/by-nc/4.0
Digital citizenship and student-teacher readiness: insights from Malaysia
Introduction. Digital citizenship is increasingly recognised as vital for teacher education, yet its integration in Malaysia remains fragmented. This study investigates how digital citizenship is conceptualised, taught, and experienced in Malaysian Institutes of Teacher Education (ITEs). Method. A convergent parallel mixed-methods design was adopted, combining a survey of 425 student-teachers across four ITE campuses, interviews with eight lecturers and document analysis of national education policies, UNDP Digital Transformation Framework and course summaries. Analysis. Survey data were analysed descriptively, while interviews and documents were thematically coded using a hybrid deductive-inductive coding framework informed by Ribble’s nine elements of digital citizenship. Triangulation across strands enabled identification of convergences and gaps. Results. Student-teachers showed near-universal access to devices and high online activity but inconsistent verification practices, limited ethical reasoning and emotional reliance on digital connectivity. Lecturers displayed conceptual ambiguity and lacked training, while curricula reflected fragmented integration of digital citizenship. Conclusion(s). The study identifies a policy-practice gap, highlighting the need for cross-curricular integration, dedicated modules, and lecturer training. It stresses digital well-being as a professional competency and situates Malaysia’s case within global debates on preparing reflective, ethical, and participatory digital citizens for the 21st century.
Copyright (c) 2026 Rini Azrina Zabri https://creativecommons.org/licenses/by-nc/4.0
Privacy risk assessment method incorporating sensitivity and correlation with empirical study
Introduction. User-generated content (UGC) has emerged as a prominent vector for privacy breaches, especially due to the context-dependence of data sensitivity and vulnerabilities introduced by data correlations. These challenges highlight the growing limitations of traditional assessment methods. Method. This study proposes a privacy risk quantification method integrating both attribute sensitivity and inter-attribute association, with an experimental validation conducted on the ‘Friend Identification’ section of the https://muchong.com. A BERT-BiLSTM-CRF deep learning model is utilized for the automatic identification of attributes from unstructured text. Using a predefined privacy data lexicon, attribute sensitivity is quantified, and pointwise mutual information (PMI) is introduced to measure attribute associations. Combined with a privacy subject identification factor, these elements collectively quantify privacy risk values, followed by risk level classification. Results. Ablation experiments and manual validation have confirmed the feasibility of the proposed scheme, demonstrating its capability to identify, assess, and classify privacy risks in unstructured textual data with broad applicability. Conclusion(s). The study validates the proposed solution theoretically, technically, and empirically, overcoming the limitations of traditional isolated-field evaluation paradigms. The method can be extended to high-sensitivity domains such as healthcare and finance, providing a basis for dynamic, risk-informed classification policies.
Copyright (c) 2026 Ruili Geng , Tiantian Zhang , Sentao Li , Yishuai Xu https://creativecommons.org/licenses/by-nc/4.0
Framing data inequality as an information justice lens: Access, representation, and control in algorithmic decision-making
Introduction. This study investigates how data inequality manifests within algorithmic systems and explores how an information justice framework can be applied to reframe these inequalities. Method. In-depth interviews were conducted with 36 participants representing three distinct roles — algorithm design-related users, algorithm-for-work users, and algorithm-for-daily-life users — within the Chinese internet context. The qualitative data gathered capture their perceptions and lived experiences of data inequality in algorithmic systems. Analysis. Thematic analysis was employed to identify and categorize forms of data inequality. These categories were then interpreted through the lens of information justice using the data, information, knowledge, wisdom (DIKW) model to illuminate their moral implications. Results. The study provides empirical evidence for three forms of data inequality — access inequality, representation inequality, and control inequality. Each of these undermines information justice in distinct ways, particularly with respect to iParticipatory justice and iRecognitional justice, manifesting as exclusion from participation, distortion of identity, or erosion of data sovereignty. Conclusion. Data inequality represents a systematic violation of information justice. Reframing data inequality as an information justice lens not only advances research on digital inequality but also deepens theoretical discussions at the intersection of data ethics, algorithm studies, and information science.
Copyright (c) 2026 Shiwei Jia, Hui Yan, Jia Tina Du https://creativecommons.org/licenses/by-nc/4.0
Competing visions of ethical AI: a case study of OpenAI
Introduction. AI Ethics is framed distinctly across actors and stakeholder groups. We report results from a case study of OpenAI analysing ethical AI discourse. Method. Research addressed: How has OpenAI’s public discourse leveraged ‘ethics’, ‘safety’, ‘alignment’ and adjacent related concepts over time, and what does discourse signal about framing in practice? A structured corpus, differentiating between communication for a general audience and communication with an academic audience, was assembled from public documentation. Analysis. Qualitative content analysis of ethical themes combined inductively derived and deductively applied codes. Quantitative analysis leveraged computational content analysis methods via NLP to model topics and quantify changes in rhetoric over time. Visualizations report aggregate results. For reproducible results, we have released our code at https://github.com/famous-blue-raincoat/AI_Ethics_Discourse. Results. Results indicate that safety and risk discourse dominate OpenAI’s public communication and documentation, without applying academic and advocacy ethics frameworks or vocabularies. Conclusions. Implications for governance are presented, along with discussion of ethics-washing practices in industry.
Copyright (c) 2026 Melissa Wilfley, Mengting Ai, Madelyn Rose Sanfilippo https://creativecommons.org/licenses/by-nc/4.0
Did I really agree to that?: making sense of policies you didn’t read with models that actually did
Introduction. While Privacy Policies and Terms of Service (ToS) are intended to inform users; they often overwhelm, mislead, and confuse in practice. This work investigates automated techniques for analyzing such legal documents, with the goal of supporting user comprehension and regulatory auditing. Method. We use expert-driven annotations from Terms of Service; Didn’t Read (ToS;DR) to train classification models that assign case labels to individual sentences. We also develop a classifier to distinguish document types: Privacy Policy, ToS, or other legal text. Analysis. Models were evaluated using F1 score, and we compared traditional fine-tuned models (RoBERTa, PrivBERT) against GPT-4 Turbo. We then applied the best-performing models to real-world policies to uncover conceptual overlaps between Privacy Policies and ToS. Results. Our case classifier achieved a 0.73 F1 score, while the document-type classifier reached 0.79. GPT-4 performed worse on case classification (0.58 F1). We found that GDPR-relevant clauses often appear in both Privacy Policies and ToS, blurring distinctions and raising risks for user misinterpretation and regulatory non-compliance. Conclusion. By surfacing hidden structures and overlapping clauses, our system enhances transparency and supports digital literacy by increasing accessibility of complex documents. This work lays the foundation for tools that promote user agency and platform accountability.
Copyright (c) 2026 Shikha Soneji, Mitchell Hoesing, Sujay Koujalgi, Jonathan Dodge https://creativecommons.org/licenses/by-nc/4.0
From privacy concerns to digital literacies: negotiating trust and authenticity in AI-mediated student records systems
Introduction. This study examines how students negotiate privacy concerns in AI-mediated student record systems, focusing on Xuexin.com, China’s national digital archive of university student records. Using the antecedent–privacy concern–outcome (APCO) model, privacy practices are framed as forms of information literacy tied to authenticity, trust, and digital inclusion. Method. Semi-structured interviews were conducted with fifteen students and recent graduates (aged 20–27) between May and July 2025. Interviews lasted 30–60 minutes, face-to-face or online, guided by APCO categories while allowing emergent themes. Analysis. Directed content analysis with NVivo was applied. APCO codes were refined to include themes of algorithmic opacity, fragile trust, and resistance. Reliability was checked by re-coding 20% of transcripts. Results. Four antecedents (breaches, literacy, risk, and trust) shaped behaviours from reluctant compliance to withdrawal. Privacy literacy emerged as unevenly distributed, with implications for authenticity and digital inclusion. Conclusion. Privacy in digital student records systems is best understood as a fragile, uneven literacy practice. Its unequal distribution risks deepening exclusion, raising questions about authenticity, trust, and the conditions for a digitally enlightened society.
Copyright (c) 2026 Yang Lu , Yunjie Tang , Yijia Song https://creativecommons.org/licenses/by-nc/4.0
Information and death: towards a conceptual framework for studying information as it relates to dying, death, mourning and digital afterlife
Introduction. This paper presents a work in progress to develop a conceptual framework for studying information as it relates to the phenomenon of death, including dying, mourning, legacy, and digital afterlife. Method and Analysis. A framework is derived using the results of a previously published systematic review of literature at the intersection of death and information management (Dinneen et al., 2024). Specifically, we conceptualised the factors identified in the review into the information and death framework. Results. We present and discuss the first component of the framework: six key perspectives that represent different vantage points from which to view the problem, each with their own focus and concerns. Conclusion(s). Though still in development, the framework looks promising for supporting empirical and theoretical research on pressing and global information-related issues surrounding the experience of loss, death, dying and digital afterlife.
Copyright (c) 2026 Maja Krtalić, Jesse Dinneen https://creativecommons.org/licenses/by-nc/4.0
Unveiling moral development in generative AI chatbots
Introduction. Guided by Kohlberg’s theory, this paper aims to investigate the moral development levels of GAI chatbots. Method. The Defining Issues Test Version 2 (DIT-2) was applied to assess the reasoning stages of four GAI chatbots, namely, Claude 4, Claude 4.1, ChatGPT 4o, and ChatGPT 5. Analysis. A total of 240 data points (6 indices × 10 runs × 4 chatbots) were analysed using the Coefficient of Variation (CV), Welch’s ANOVA, and Games-Howell test. Results. The results showed that Claude 4 was the most consistent in responding to moral dilemmas, whereas ChatGPT 4o was the least. Compared with Claude 4.1 and ChatGPT 4o, Claude 4 and ChatGPT 5 exhibited similarly higher levels of postconventional reasoning and moral differentiation. Conclusion(s). This paper advances the literature on AI ethics by shifting the focus from outcome-oriented evaluations to developmental levels of reasoning. Additionally, it extends Kohlberg’s theory of moral development into the domain of GAI. Practically, this study helps users understand the moral reasoning of the latest chatbots for more informed use. It also guides developers in improving models toward greater transparency and ethical alignment.
Copyright (c) 2026 Jiayu Han , Alton Y.K. Chua https://creativecommons.org/licenses/by-nc/4.0
Modelo informacional da carteira de identidade nacional (Brasil): uma leitura a partir da diplomática arquivística contemporânea (Information model of the national identity card (Brazil): a reading from contemporary archival)
Introduction. The national identity card information model (MI-CIN in Brazilian Portuguese) is the conceptual representation of the information structure that comprises the national identity card, a new personal identification document for Brazilian citizens. The objective of this article is to analyse the MI-CIN from the perspective of documentary genesis as addressed by contemporary archival diplomatics. Method. This qualitative study used bibliographic and documentary research as research techniques to operationalize knowledge. Analysis. The analysis included: a foundation for the concept of personal identification document, situating it within the domain of contemporary archival diplomatics; a history of the identity card in Brazil; and the conception of the information model and the structuring logic of the MI-CIN. Results. The MI-CIN systematizes the formal elements of a document's configuration, based on the nature of the act that originated it: civil identification. The MI-CIN characterization demonstrates the structure that the final document should present, both as a unifying attribute and as a guarantee of its authenticity. Conclusion(s). It was possible to establish the relationship between information model and contemporary archival diplomatics, based on an innovative approach that analyzed the documentary genesis of CIN through its information model.
Marcia Cristina de Carvalho Pazin Vitoriano
Copyright (c) 2026 Thiara dos Santos Alves , Marcia Cristina de Carvalho Pazin Vitoriano , Juliana Loureiro Alvim Carvalho https://creativecommons.org/licenses/by-nc/4.0
A study on the correlation mechanism between knowledge convergence characteristics and short- and long-term patent impact
Introduction. This study aims to reveal the underlying mechanisms linking knowledge convergence characteristics in different technological domains with the short- and long-term impact of patents. Method. Using a negative binomial regression model, it systematically examines the differentiated effects of scientific knowledge breadth, scientific knowledge depth, technological knowledge breadth, and technological knowledge depth on the short- and long-term impact of patents. Analysis. This framework enables precise characterization of structural features in knowledge absorption and recombination and provides the basis for quantifying heterogeneous effects of knowledge convergence. Results. The breadth of knowledge generally enhances patent influence and exhibits an inverted U-shaped relationship, suggesting that moderate diversity and integration increase patent value. In contrast, the effect of knowledge depth varies across fields and time scales: scientific depth in computer technology shows a long-term U-shaped pattern, depth in semiconductors has a positive long-term effect, while technological depth in biotechnology is largely negative. Conclusion(s). The innovation cycles and knowledge application mechanisms in different fields determine the configuration patterns of knowledge breadth and depth: fast-iteration fields rely more on short-term diffusion driven by breadth, while long-cycle fields emphasize the long-term value of deep accumulation.
Copyright (c) 2026 Jing Ma, Liyuan Li, Yaohui Pan https://creativecommons.org/licenses/by-nc/4.0
Unraveling technology diffusion through dynamic network and multi-dimensional mechanism analysis: evidence from natural language processing
Introduction. Understanding factors influencing technology diffusion is vital for optimizing technological environments and fostering innovation. Existing studies often overlook temporal dependence and lack multidimensional mechanism analysis. This study addresses these gaps by introducing a dynamic network perspective to analyze technology diffusion. Method. We developed a framework that integrates topic extraction with dynamic relationship modeling. Using patent data, BERTopic was applied to identify technological topics and construct cross–time-slice diffusion networks. Social network analysis captured evolutionary patterns, while the temporal exponential random graph model (TERGM) jointly examined endogenous network structures, actor–relation effects, and exogenous factors. Analysis. The natural language processing field was selected as a case study. Diffusion dynamics and mechanism factors were investigated through quantitative modeling of temporal networks. Results. The network has become more cohesive yet decentralized. Core nodes remain but their bridging role weakens. Reciprocity strongly promotes diffusion. Topic influence, novelty, and knowledge quality positively drive relationship formation, while knowledge breadth and depth affect only the sender effect. Conclusions. This study integrates dynamic networks with multidimensional mechanism analysis, bridging gaps in temporal evolution and mechanism exploration, and providing a reusable framework and empirical reference for technology diffusion research.
Copyright (c) 2026 Junhao Yang, Haiyun Xu, Robin Haunschild, Shuying Li, Chunjiang Liu, Xueli Yu https://creativecommons.org/licenses/by-nc/4.0
Multi-viewpoint knowledge graphs for minority cultural heritage: the case of online Jewish museum collections
Introduction. This study addresses the representation of ethnic minority cultures in online museum collections, which often reflect diverse viewpoints. We propose a data-driven methodology to construct a large-scale multi-viewpoint knowledge graph, using Jewish cultural heritage as a case study. Method. We developed an LLM-based pipeline that combines object typing, named entity recognition, relation extraction, enrichment, and clustering. Results. An analysis of 647,951 records and 178,444 extracted subjects from the collections of Jewish museums across the globe revealed diverse thematic emphases: Israel and the Netherlands prioritised religious themes, while others highlighted everyday life. Surprisingly, only Australia emphasised the Holocaust. Conclusion(s). The central contribution of this study is the development of a knowledge organisation system capable of tracing major trends and identifying patterns in the polyvocality of perspectives. The methodology provides quantifiable, scalable analysis of multi-viewpoint cultural heritage, extendable to other minorities.
Copyright (c) 2026 Sara Minster , Maayan Zhitomirsky-Geffet , Inna Kizhner https://creativecommons.org/licenses/by-nc/4.0
Revising the research data lifecycle: Evidence from oceanography
Introduction. This research examines temporal elements of data management for ocean science researchers funded by the United States’ National Science Foundation (NSF). By uncovering data practices for sharing data, this paper finds that researchers’ experience diverges significantly from traditional models of research data lifecycle. Method. Corpus creation of 379 Data Management Plans (DMP) from NSF funded oceanography awards between 2011-2021 and 34 semi-structured interviews with principal investigators (PIs) and data managers from purposive and snowball sampling. Analysis. Qualitative coding of both DMP documents and interview transcripts using MaxQDA software using a codebook drawn from Adam’s (1998) timescapes framework and themes developed through inductive qualitative analysis of the interview transcripts. Results. Research data management to support sharing data lacks an established place in the organization of research practice and often leads to end-loaded project data management. Three ways that researchers are developing new practice-time profiles include creating routines, automating workflows, and anticipating the data practices of reusers. Conclusion(s). Data management for sharing is not only constrained but also actively shaped through time. Research data lifecycles need to place more emphasis on the actors within this lifecycle.
Copyright (c) 2026 Yubing Tian, Thomas Struett, Amelia Acker, Megan Finn https://creativecommons.org/licenses/by-nc/4.0
Envisioning the process: Lessons from developing institutional OER repositories in Vietnam
Introduction. This study investigates the development of institutional open educational resources repositories (IOERs) in Vietnamese higher education. While OER adoption has been widely examined at the level of students and lecturers, little is known about institutional processes for developing repositories, particularly in resource-constrained contexts. Method. A qualitative approach was adopted, using semi-structured interviews with 20 participants, including IOER leaders, OER champions, university administrators, faculty members, and library administrators and staff from four major Vietnamese cities. Participants were identified through purposive and snowball sampling to ensure they had direct involvement in OER initiatives. Analysis. Interview transcripts were analysed using inductive content analysis supported by NVivo. Coding was data-driven, with emerging categories interpreted through Fullan’s educational change framework, focusing on the phases of initiation and implementation Results. The study identifies four campus stakeholder groups: project implementers, content producers and users, facilitators, and university leaders. Two phases are highlighted: initiation, centred on leadership approval, and implementation, involving management, awareness-raising, use, and content creation. Conclusions. IOER development in Vietnam should be understood as an educational change process rather than a technical initiative. Libraries play a central role, but success depends on cross-unit collaboration, visionary leadership, and strategies to build awareness and engagement.
Copyright (c) 2026 Vi Truong, Bao Tran Chau https://creativecommons.org/licenses/by-nc/4.0
Intermediary or gatekeeper? Defining content responsibility boundaries of open research data platforms
Introduction. Open research data platforms often position themselves as ‘intermediaries’ yet exercise ‘gatekeeper’ power through design and policy choices. Despite extensive content governance scholarship on social media platforms, research data platforms remain underexplored. Method. I employ reflexive thematic analysis of publicly available documents from three platforms: Zenodo (publicly funded generalist), ICPSR (membership-based disciplinary), and Mendeley data (commercial publisher-integrated). This comparative approach examines how distinct platform types navigate content responsibility. Results. Platforms transcend binary intermediary-gatekeeper distinctions through multi-dimensional responsibility allocation. I construct two themes: curatorial boundary-drawing between form and substance, where platforms moderate formal compliance while adopting different approaches to scientific curation; and selective responsibility allocation, whereby platforms delegate immediate legal liability to users while internalizing long-term archival stewardship. Conclusion. I contribute a framework distinguishing ‘epistemic responsibility’ from ‘archival responsibility’ and propose a typology of infrastructural intermediary, disciplinary gatekeeper, and commercial hybrid models. I further argue for ‘directional flexibility,’ where gatekeepers can scale by adopting intermediary functions, whereas intermediary platforms face economic barriers to adopting substantive gatekeeping.
Copyright (c) 2026 Zhengzheng Tian https://creativecommons.org/licenses/by-nc/4.0
Exploring institutional change in a knowledge commons: a longitudinal institutional analysis of journal policies
Introduction. Studies on shared information and its governance, known as knowledge commons, are closely related to open access (OA) initiatives. Understanding institutional changes is critical for knowledge commons, and systematic methods for such analyses are in demand. This study applies such a method to PLOS ONE, a typical OA mega journal, to explore the characteristics of the institutional change of the journal. Method. This study introduces a research approach of combining content analysis based on Institutional Grammar, a tool for examining the syntactic structure of institutions, with data collection through the Internet Archive’s Wayback Machine, focusing on policies and guidelines of PLOS ONE. Analysis. Institutional changes of PLOS ONE were analysed by comparing institutional complexity and stringency at two time points. Results. The analysis revealed that the institutions run by PLOS ONE have evolved toward greater complexity and stringency. This change explains an adaptation to environmental changes in scholarly-communication ecosystems over the past few decades. However, this may also impose additional burdens, especially those on PLOS ONE authors. Conclusions. The findings support the existing hypothesis on the institutional change in knowledge commons and offer new hypothetical insights into its impact on actors.
Copyright (c) 2026 Kai Nishikawa https://creativecommons.org/licenses/by-nc/4.0
Amulets, boxers, and cybersecurity: influencer metaphors in VPN advertising and the communication of cybersecurity risk
Introduction. VPNs primarily establish encrypted tunnels for network traffic and mask users’ IP addresses; they do not inherently block malware, phishing, or denial-of-service attacks. Yet advertising content often portray VPNs as comprehensive security solutions, blurring public understandings of what these tools can and cannot do. This exploratory study examines how YouTube influencers in Taiwan frame VPNs in sponsored content and communicate cybersecurity risks. Method. This study employs qualitative content analysis of sponsored VPN videos published by top Taiwanese YouTube influencers. Data include 20 videos and 99 close-watching observation notes documenting narrative strategies in promotional contexts. Analysis. Using open coding and iterative qualitative analysis, we examine influencer narratives across four analytical dimensions informed by risk communication frameworks: technical accuracy, risk translation, metaphorical strategies, and audience engagement. Results. This study identifies several recurring strategies in VPN-sponsored videos, including simplifying technical descriptions, reframing risks as consumer disadvantages, and using metaphors or everyday scenarios to make VPNs more relatable. While these tactics increased accessibility and entertainment value, they also risked obscuring the conditional and limited scope of VPNs. Conclusion. The findings show how vernacular metaphors and promotional framings shape public understandings of digital security, extending cybersecurity communication research beyond news or policy discourse.
Copyright (c) 2026 Yu-Wen Huang, Yu-Jie Lin, Kai-Hsiang Chou, An-Jie Li, Tsai-Hsuan Hsieh, Li-Fei Kung, Wie Jeng https://creativecommons.org/licenses/by-nc/4.0
Comunicação científica na era digital: o case da SciELO Brasil e seus video abstracts
Introdução. Este artigo analisa a adoção de video abstracts pela SciELO Brasil em seu canal no YouTube como estratégia para a Ciência Aberta, explorando a transição de um modelo de distribuição para um de circulação do conhecimento em rede. Método. Realizou-se uma análise metodológica mista (quantitativa longitudinal e de conteúdo) sobre um corpus de 727 vídeos publicados entre agosto de 2012 e março de 2025. Análises. Os vídeos foram categorizados para examinar a frequência de publicação, as mudanças na estratégia de conteúdo e as métricas de engajamento do público. Resultados. Os dados revelam a evolução do canal, de um repositório de eventos longos para uma plataforma de disseminação de vídeos curtos. A partir de 2019, a publicação de ‘Resumos de Artigo’ tornou-se o foco principal, representando 88,5% do conteúdo anual em 2022. Conclusão. A SciELO Brasil está na vanguarda da comunicação científica digital, usando o video abstract para aumentar a acessibilidade e o impacto da pesquisa. A iniciativa fortalece a Ciência Aberta, mas a qualidade heterogênea dos vídeos aponta para a necessidade de investir na literacia de mídia dos pesquisadores.
Copyright (c) 2026 Brasilina Passarelli , Adeilson Toledo Torres https://creativecommons.org/licenses/by-nc/4.0
Immersive quality control for 3D data curation
Introduction. We report quantitative findings from a multi‑site experiment evaluating the impact of immersive viewing (XR) on routine quality control (QC) tasks in academic labs regularly producing 3D content across the United States. Method. 29 participants were recruited to complete orientation, error‑detection, and comparison tasks under two viewing conditions: Meta Quest 3 (XR) and iPad tablet computer (control). Time‑to‑completion (TTC) and accuracy performance were measured. Post-condition NASA‑TLX and SUS captured perceived cognitive load and system usability. Analysis. We ran one‑tailed within‑subjects t‑tests for TTC, TLX, and SUS with Holm–Bonferroni correction; accuracy was modeled via logistic regression (participant as random effect); Cohen’s dz reported. Results. XR demonstrated faster TTC (M = 11.90 s) than tablet (M = 20.42 s; Holm‑corrected p = .0129; dz = .56) and lower cognitive load (TLX) (14.6 vs. 18.92; Holm‑corrected p = .026; dz = .46). Accuracy (.76 vs .77) and usability (SUS) (83.9 vs. 80.2) did not differ significantly across conditions. Conclusion. Immersive review of scholarly 3D assets shows promise as a tool for supporting 3D data curation workflows. Using the XR platform was found to reduce time and perceived effort for 3D creators on QC tasks without impacting accuracy or usability.
Copyright (c) 2026 Matt Cook, Hannah Hok Kim, Helen He, Zack Lischer-Katz https://creativecommons.org/licenses/by-nc/4.0
Safe but scripted: uncovering second-order bias in LLM LGBTQ+ storytelling
Introduction. This study investigates how large language models (LLMs) narrate everyday LGBTQ+ romance. Method. Using a matrix of 10 prompts with parallel versions for male-male (M-M), female-female (F-F), and male-female (M-F) couples, we generated 120 textual outputs from four leading LLMs (GPT-5, Claude 4 Sonnet, Llama 4, and Deepseek-V3). Analysis. We performed a qualitative analysis on the corpus, first auditing for overt biases (e.g., relationship downgrading) before using comparative thematic analysis to identify the stereotypical narrative scripts systematically applied to each couple pairing. Results. No overt bias was found, establishing a baseline of formal equality. However, we discovered a significant second-order bias: models consistently deploy three distinct scripts. Female-female couples are cast in an ‘Emotional Haven’ trope, male-male couples as ‘Future Builders,’ and male-female pairs follow a traditional ‘Default Template.’ Conclusion(s). LLMs currently achieve safety at the cost of authenticity, resulting in a ‘benevolent stereotyping’ of LGBTQ+ representation. This finding reveals the limits of current evaluation paradigms, which audit for overt harm but fail to measure narrative equity, as sanitised tropes replace diverse realities.
Copyright (c) 2026 Huiqian Lai https://creativecommons.org/licenses/by-nc/4.0
Enabling embodied metaphors in new media arts: a multi-sensory augmented reality approach
Introduction. This study examines how multi-sensory augmented reality (MSAR), and embodied metaphor theory (EMT) can enhance immersion and comprehension in new media art. The installation, the moon knows, embodies four moon metaphors—romance, time, reunion, and self-discovery—to explore embodied interaction and audience perception. Method. The system combined a tangible moon interface, Microsoft HoloLens 2, projection, and sensors linked to Unity3D and Arduino. Fifteen participants experienced four interactive chapters and provided feedback through questionnaires and semi-structured interviews. Analysis. Quantitative data measured immersion, engagement, and understanding, while qualitative coding of interviews identified themes in multisensory interaction and metaphor perception. Results. It proved possible to integrate MSAR with EMT in a new media artwork and to demonstrate that immersion and engagement were enhanced through embodied interaction. Results also revealed variations in how different metaphors were understood, with some concepts more intuitively grasped than others. Conclusion(s). MSAR combined with EMT effectively enhances immersion and engagement in new media art. While abstract metaphors need clearer articulation, The moon knows shows how embodied multisensory design can foster emotional resonance and broaden interpretive possibilities. The potentials of MSAR being used in libraries and museums are discussed.
Copyright (c) 2026 Weiyue Lin, Xiao Hu https://creativecommons.org/licenses/by-nc/4.0
Preserving creative process in the digital age: Findings from a survey of contemporary composers
Introduction. Digital tools have become ubiquitous in the process of music composition and documentation of composers’ lives and careers. This material and subsequent scholarship are at risk due to the obsolescence of hardware and software, fragility and variety of digital file formats, media prone to degradation. This paper presents survey results on composers’ process and knowledge of preservation practices. Method. The survey was designed in GoogleForms and distributed through email to music theory and composition faculty at Big10 universities, major conservatories, and professional organization listservs. The survey assessed compositional workflows and respondents’ knowledge and implementation of preservation practices through quantitative and free-response qualitative questions. Analysis. The survey generated qualitative data, examined thematically; quantitative responses were analysed for trends. Results. The results demonstrate a need for a central, open resource to guide composers through implementation of preservation practices to ensure longevity of their work. Conclusion. This survey is the first to bridge the disjunction between composers’ creative process and preservation practices. Results illustrate wide usage of digital tools and proprietary file types and indicate a concerning lack of preservation knowledge. It will inform a toolkit that offers guidance on long-term preservation, to bring composers into confident stewardship of their creative legacies.
Copyright (c) 2026 Jessica Grimmer, Stephanie Akau https://creativecommons.org/licenses/by-nc/4.0
An asymmetric echo: tracing social sentiment through economic cycles in a large-scale corpus of American newspapers
Introduction. This study investigates the relationship between social sentiment and macroeconomic cycles in the United States from 1919–1937, a period of profound economic transformation. It aims to quantify and analyse public emotion dynamics across the economic expansion period, the downturn period, and the recovery period, seeking to identify patterns in how macrosocial and economic factors influence social sentiment. Method. A computational approach was employed, using natural language processing (NLP) and the LIWC lexicon to conduct sentiment analysis on a large-scale corpus of digitised historical newspapers from the Chronicling America database. Analysis. Quantitative sentiment tendencies were compared using analysis of variance (ANOVA) and independent samples t-tests to identify significant variations and correlations across the distinct economic periods. Conclusion(s). Findings reveal an asymmetric correlation: while positive sentiment is pro-cyclical, negative sentiment was counterintuitively suppressed during economic downturns. We attribute this paradox to a dual mechanism of individual psychological compensatory control and macro-level governmental expectation management. This research provides a novel framework for historical sentiment analysis, challenging conventional narratives about public responses to crises and offering insights for contemporary public opinion governance.
Copyright (c) 2026 Zihan Zeng , Yingyu Wang, Xiaofan Ran , Qi Li Li , Liang Zhao https://creativecommons.org/licenses/by-nc/4.0
Exploring a VR safety training prototype for active shooting emergency preparedness: Demonstration and preliminary evaluation
Introduction. Immersive experiences through virtual reality (VR) offer opportunities to create authentic yet safe learning environments for high-stakes training contexts. In this paper, we present a serious game virtual reality safety training prototype for active shooting emergencies in schools, titled Second Chance. This gamified training application aims to improve students' decision-making during active shooter emergencies based on the ALICE (alert, lockdown, inform, counter, and evacuate) method. Method. The prototype was developed for Oculus Go, with game mechanics such as progressive level design, interactive tutorial, NPC collaboration, and performance-based progression. Analysis. We conducted pre- and post-training questionnaires (N = 18) measuring anxiety, motivation, readiness, usability, presence, and perceived effectiveness. Results. Results showed low pre-training anxiety levels (M = 2.236), moderate to high pre-training motivation (M = 3.861) and post-training perceived training effectiveness (M = 3.824) on a 5-point scale relative to the scale midpoint. Conclusion. This preliminary evaluation demonstrates the prototype's potential as an entry-level ALICE training tool and provides insights for future comprehensive serious games and gamified VR training research in educational emergency preparedness contexts.
Copyright (c) 2026 Daniel Zuniga-Vazquez , Ren Boz https://creativecommons.org/licenses/by-nc/4.0
The disciplinary diversity shrinkage — the experience of Colombian social science research groups
Introduction. This study examines disciplinary diversity within 1,105 Colombian social science research groups between 2013 and 2021. While existing literature focuses on STEMM in high-income nations, this research addresses the knowledge gap in middle-low-income contexts where resource constraints influence scientific resilience. Method. Data were retrieved from MinCiencias national assessments. The study used the DIV diversity index to evaluate three dimensions: variety, balance, and disparity. Analysis. The longitudinal analysis categorized groups by their national ranking (A1, A, B, C, and Recognized). Trends in the DIV index were correlated with team size and hierarchical structures to identify factors influencing interdisciplinary composition. Results. Findings indicate a significant decline in disciplinary diversity among top-tier groups (A1 and A) over time. While lower-ranked groups maintained more stable profiles, their overall diversity remained low. Increased team size and hierarchical concentration in elite groups appear to hinder disciplinary integration. Conclusions. The reduction in diversity suggests that current national assessment policies may inadvertently discourage interdisciplinarity. Reforms are necessary to foster flatter, more innovative team structures. Future research should consider open bibliometric data to link these diversity trends to specific research impacts.
Copyright (c) 2026 Julian D. Cortes https://creativecommons.org/licenses/by-nc/4.0
Hybrid weak supervision model with manual and pseudo labels: a novel approach for scientific text mining
Introduction. Although deep learning has advanced scientific text mining, the high cost of manual annotation remains a significant bottleneck. To address this, we propose a hybrid weak supervision model (HWSM) that balances manual annotation costs, computing resources, and model performance. Method. HWSM integrates a manually annotated subset with LLM-generated pseudo-labels and trains a deep learning model on this hybrid corpus, leveraging both human expertise and large-scale automated labeling in entity recognition tasks. Analysis. The model was evaluated against supervised deep learning and few-shot LLM baselines on 5,000 LIS papers, measuring precision, recall, F1, and cost-performance trade-offs. Results. HWSM achieves a competitive F1-score (within 0.01 of GPT-4.1) while significantly reducing labeling and inference costs. Optimal performance is observed when incorporating 80% pseudo-labeled data. Conclusion. HWSM provides a robust, cost-effective solution for large-scale scientific entity recognition. It is particularly suited for scenarios with limited labeling budgets, offering a practical alternative to resource-intensive deep learning or expensive LLM-only approaches.
Copyright (c) 2026 Shengli Deng , Rongrong Xiang , Qiuyu Zhu , Fang Chen https://creativecommons.org/licenses/by-nc/4.0
Evaluating software academic impact in biomedical research based on large-scale full-text analysis
Objective. Analysing patterns of academic software mentions and their academic impact is essential for understanding the scholarly ecosystem and optimising research resources. Methods. This study focuses on the biomedical domain and investigates the prevalence and impact of software entities in scientific research. Rather than treating impact as a causal effect on research outcomes, we operationalise software impact as its scholarly presence, measured through the frequency of mention. Based on 1,500,334 articles from PubMed Central Open Access (PMC-OA), we collected disambiguated software entities mentioned in the full texts and extracted their features, including mention time, in-text location, and research subfields. Results. Overall, the impact of software in biomedical research continues to grow, with programs such as SPSS, GraphPad, and Mega demonstrating high academic influence. Within papers, software influence is concentrated in the Methods section and is dominated by general-purpose statistical tools, while other sections display greater diversity. Across fields, domains with high-software mention tend to rely on general-purpose software, whereas more specialised domains adopt software tailored to specific biomedical tasks. Conclusion. By tackling these questions, this study advances a systematic understanding of software role in biomedical research and provides a basis for further methodological refinement and empirical analysis.
Copyright (c) 2026 Yuzhuo Wang , Heng Zhang , Huahao Hu , Yi Zhao https://creativecommons.org/licenses/by-nc/4.0
OpenAlex in focus: Metadata quality of publication type and language fields in an open peer review corpus
Introduction. OpenAlex is widely used as a free bibliographic database for bibliometric and scholarly communication research. Despite its openness and coverage, its metadata contains inconsistencies that require systematic cleaning. This study examines metadata quality in OpenAlex, focusing on publication type and language. Method. Publications on open peer review were retrieved from OpenAlex. After filtering and deduplication, 6,640 records were manually checked. Document type and language fields were cross-verified with publisher sources, while Crossref publication types were also collected for comparison. Analysis. Manual classification was harmonised across categories to ensure comparability. The main focus was to evaluate the agreement between OpenAlex and manual classifications of type and language, and to assess the consistency of Crossref publication types with both. Results. Of 6,640 records, 2,878 (43%) showed publication type discrepancies, with ‘Article’ most often misused. Crossref aligned more closely with OpenAlex in broad categories but diverged from manual verification. Additionally, 222 records (3.3%) had language mismatches, often English labels wrongly assigned to non-English works. Conclusion(s). OpenAlex is a valuable infrastructure, yet its metadata for publication type and language shows notable inconsistencies. Researchers should apply systematic cleaning and validation before using OpenAlex or similar databases.
Copyright (c) 2026 Güleda Doğan , Ayça Nur Sezen https://creativecommons.org/licenses/by-nc/4.0
How do users respond to AI fact-checkers?
Introduction. This paper aims to empirically validate a conceptual model that explains how users respond to AI fact-checkers originating from different countries. Guided by the country-of-origin effect, source credibility theory, and elaboration likelihood model, the model comprises five variables, namely, AI fact-checkers, fact-checker source credibility, perceived credibility of flagged news, issue involvement, and AI literacy. Method. An online experiment was conducted to examine how participants responded to AI fact-checkers from two countries, namely the United States of America (U.S.) and China. Analysis. A total of 139 responses were collected in this study. Data was analysed using a one-way analysis of variance (ANOVA), PROCESS Model 4 and 9. Results. The results showed that AI fact-checkers (country of origin: U.S. vs. China) directly influenced the perceived credibility of flagged news. Fact-checker source credibility mediated the effects of AI fact-checkers. Issue involvement moderated the indirect effect of AI fact-checkers on perceived credibility of flagged news via fact-checker source credibility, whereas AI literacy did not. Conclusion(s). Theoretically, this paper adds to the scholarly understanding of the effectiveness of AI fact-checkers from different countries of origin. Practically, it highlights the importance of considering the country-of-origin effect when deploying AI fact-checkers for social media platforms.
Copyright (c) 2026 Alton Y.K. Chua, Jiayu Han https://creativecommons.org/licenses/by-nc/4.0
Inclusive media and information literacy (IMIL): Building a framework for an age of preparedness and responsibilisation
Introduction. In policy and political debate, media and information literacy (MIL) is increasingly framed as a civic responsibility and a strategic response to the contemporary ‘information crisis’, marked by disinformation and digital insecurity. This positions MIL as essential to democratic resilience and national security but risks excluding individuals who lack the resources or capacities to meet these demands. Method. This paper develops a conceptual framework for critically and constructively analysing the consequences of placing the responsibility of correct information handling on individuals in times of crises and securitisation. Four theoretical building blocks – critical media and information literacy; critical pedagogy; disability studies, and theories of resilience – are used to construct the framework inclusive media and information literacy. Results. The framework presented will allow for an expansion of current MIL research on digital inequalities by bringing together and explicitly highlighting power relations, institutional framings, and the situated agency of vulnerable groups in times of information crisis and heightened preparedness. Conclusion(s). The paper emphasizes the practical relevance of the framework for popular education and public libraries, which increasingly support MIL and democratic resilience as part of the civil defence.
Copyright (c) 2026 Hanna Carlsson, Lisa Engström, Lisa Olsson Dahlquist https://creativecommons.org/licenses/by-nc/4.0
Disability misinformation on Facebook: a comparison of LLM-based fact-checking tools
Introduction. Social media has become a prominent space for seeking and sharing information, but it also enables misinformation to spread. When it comes to disability-related information, such as how to apply for a Medicaid waiver, understanding the prevalence of false information on social media becomes further complicated due to varying content types. To provide an initial exploration of this problem space, we investigated misinformation propensity within disability-related Facebook groups, group factors associated with it, and the performance of AI fact-checking tools in detecting this type of information. Method. We identified target Facebook groups through a large-scale survey. From 20 public Facebook groups mentioned in the survey, we scraped 1,407 informational and fact-checkable posts. GPT-4o, GPTo1, and Originality.ai were used to classify the posts and compared. Analysis. The results were validated against the ground-truths generated manually, providing benchmarks for assessing AI tools in detecting misinformation on Facebook. Results. Our findings reveal that groups centered on developmental disabilities tend to be more vulnerable to misinformation. AI factchecking tools are generally effective in classifying accurate information but presented varying performance in detecting misinformation. Conclusion. This work provides an initial assessment of the prevalence of misinformation about disability services and the performance of LLM-based tools.
Copyright (c) 2026 Ian Prazak , Leah Padovani , Yool Lim , Julia (Hsin-Ping) Hsu , Myeong Lee https://creativecommons.org/licenses/by-nc/4.0
The role of misinformation in elder fraud: a conceptual framework
Introduction. We propose a conceptual framework to illuminate the connections between misinformation and elder fraud, especially the role of misinformation in elder fraud. Both topics have been explored in multiple areas. The connections between misinformation and elder fraud, however, are under investigated. Also, the contributions of Library and Information Science communities are limited to help older adults avoid being victims of fraud. Method. Following an integrative literature review approach, related literature on misinformation and elder fraud were collected. Analysis. This paper applies concept analysis and thematic analysis on recent literature of misinformation and elder fraud. The analysis focuses on groups of factors that moderate or mediate misinformation to elder fraud. Results. A conceptual framework on misinformation and elder fraud is developed. The framework describes the role of misinformation in elder fraud as well as related factors, including preventive factors to misinformation, antecedents to elder fraud, mediating mechanisms between misinformation and elder fraud, and protective factors to elder fraud. Conclusion(s). There are pathways through which misinformation connects to elder fraud. Strategies to detect and mitigate misinformation may help to reduce elder fraud. More investigation is needed to refine and validate the proposed framework.
Copyright (c) 2026 Jiangping Chen, Milo P. Ono https://creativecommons.org/licenses/by-nc/4.0
Nudging students to fact-check GenAI outputs: Perspectives from dual process theory and digital literacy
Introduction. Drawing from dual process theory, this study explores the acceptability of digital fact-checking nudges among GenAI users within educational contexts. The study examines differences in the perception towards GenAI fact-checking nudges with heuristic (System 1) or systematic (System 2) mechanisms, where heuristic refers to quick shortcuts and systematic to careful reasoning. This study also examines varying levels of digital literacy in GenAI usage, influencing learners' perceptions of GenAI and their responsiveness to digital nudges. Method. The study developed digital nudge vignettes tailored to educational settings and assessed their acceptability and perceived effectiveness. Data was collected from 300 university students through an online survey. Analysis. Quantitative analysis employed descriptive and t-tests comparing nudge perception between users with different levels of digital literacy. Results. Overall, the level of digital literacy was relatively high among student users. This indicates the familiarity and high tendency that GenAI users can utilise GenAI for learning. System 1 nudges were perceived more positively than System 2 nudges, and digitally literate users showed more favourable attitudes toward nudges. Conclusion(s). This study highlights the value of heuristic digital nudges and advocates for low-effort, seamlessly integrated interventions that foster fact-checking behaviors among learners when using GenAI for learning.
Copyright (c) 2026 Tran Mai Chi Nguyen, Chei Sian Lee https://creativecommons.org/licenses/by-nc/4.0
Scaffolding resilience: the influence of an iSchool’s media and information literacy courses
Introduction. We investigated the influence of an iSchool’s media and information literacy (MIL) courses on resilience to fake news. MIL interventions have been proposed to improve accuracy detection and reduce sharing intentions. This study sought to highlight attributes that facilitate resilience. Method. This preliminary study employed purposive sampling to recruit students who had taken either of the two MIL courses offered (N = 34), and those who had not (N = 32). A total of sixty-six students (N = 66) were asked to identify fake news headlines and indicate their intentions to share them through a survey via Formbricks. Analysis. This study utilised a mixed-method design. Quantitative analysis used One-Way ANOVAs to compare the accuracy and sharing scores between the two groups. Qualitative analysis was done to thematically analyse students’ evaluative strategies. Results. Findings show that MIL-educated students did not significantly differ in detecting accuracy or reducing sharing intentions compared to non-MIL students. However, MIL-educated students showed greater verification practices and more consistent standards of detection, which suggest the long-term resilience to fake news. Conclusion. Integrating MIL across curricula not only builds technical competence but also nurtures evaluative habits and ethical orientations needed to navigate today’s polarised digital publics.
Copyright (c) 2026 Frey Aura Galario , Dan Anthony Dorado , Benedict Salazar Olgado https://creativecommons.org/licenses/by-nc/4.0
Information priming for resilience: strengthening belief systems in the age of deepfakes
Introduction. As artificial intelligence advances, deepfakes have emerged as a major cybersecurity threat. Most existing research emphasises perception or algorithmic development, leaving limited understanding of how to strengthen individuals' ability to discern truth from deception and avoid victimisation. This study investigated priming effects in deepfake detection through media richness theory and dual processing theory and proposes a framework for enhancing detection strategies. Method. The experiment adopted a mixed design, with priming effect as a between-subjects factor across text, image, and multimedia modalities with embedded ground truth. Participants were assigned to the control, conceptual priming, and perceptual priming groups. Both subjective and objective data were collected to evaluate participants’ perceptions and detection performance. Analysis. Descriptive analyses examined deepfake detection accuracy and reaction time. Qualitative questions explored participants’ perceptions of deepfake detection, prior experiences, and reflections. Results. Multimedia provided rich cues that supported faster judgments, whereas lean media content demanded longer analysis. Conceptual priming promoted intuitive processes and encouraged deliberate detection strategies, while perceptual priming engaged reflective systems and heightened sensitivity to anomalies. Conclusion(s). Information priming offers a practical approach to supporting users in distinguishing authenticity from deepfakes. Perceptual priming was more effective than conceptual priming, particularly when detecting manipulations in multimedia.
Copyright (c) 2026 Yue Liu , Shuyuan Mary Ho https://creativecommons.org/licenses/by-nc/4.0
See, trust, and interact: how AI disclosure shapes high school students’ trust
Introduction. The rise of AI-generated content challenges adolescents’ ability to evaluate information and calibrate trust. This study explores how AI disclosure influences high school students’ attention, trust, and interaction with AI-generated news and comments. Method. A field experiment was conducted at a county-level high school in Henan with 60 students. Participants were randomly assigned to a control group (no disclosure) or one of two experimental groups (simple vs. detailed disclosure), enabling examination of group-level effects. Data collection combined eye-tracking, post-test questionnaires, and interviews. Analysis. Eye-tracking metrics and survey data were analysed quantitatively to examine the main and moderating effects of AI disclosure, while interview transcripts were thematically coded to provide qualitative insights. Results. Simple disclosure increased attention and trust in AI bots but reduced trust and sharing for news content. Detailed disclosure lowered engagement overall, slightly reducing trust in conversational settings and strongly reducing news-sharing. Individual differences moderated these effects: light internet users benefited most from simple labels, whereas heavy users showed stronger gains from detailed explanations in AI trust and technical understanding. Conclusion. AI disclosure produces context-dependent effects. Effective design should align label complexity with content type and user experience to provide guidance for ethical AI integration in education and social media.
Copyright (c) 2026 Nuo Chen, Zhiyuan Lai, Yichu Liu, Jia Li, Rui Wang, Pu Yan https://creativecommons.org/licenses/by-nc/4.0
Who gets blamed? Negativity bias in social media diffusion on Weibo
Introduction. This study examines negativity bias in social media diffusion by analysing Weibo discussions on women’s marriage and fertility, focusing on how opinion valence shapes diffusion dynamics. Method. We collected Weibo posts from January to March 2023, yielding 6,405 original posts and 97,090 diffusion chains after pre-processing. A large language model was used to code opinion polarity of original posts and first-level comments, and regional participant composition was measured to capture contextual heterogeneity. Analysis. Diffusion depth was operationalised as chain length. Multilevel linear mixed-effects models were employed to estimate the effects of original opinion valence, with first-level comment polarity and regional dominance specified as moderators. Results. Negative posts triggered deeper, longer diffusion while positive posts curtailed discussion spread. The stance of the first comment played a critical moderating role, that positive originals achieved wider diffusion when initial responses were negative. Regional context further moderated these effects, with eastern-user-dominated chains showing weaker amplification of negativity but stronger diffusion of positive content. Conclusion. Negativity bias strongly shapes social media diffusion, but its effects are conditional on early audience responses and regional participant composition.
Copyright (c) 2026 Tiantian Liang, Xi Wang, Mei Zhang, Jian Tang https://creativecommons.org/licenses/by-nc/4.0
Seeing past in the DREAM: a computational grounded theory analysis of comments on nostalgic videos
Introduction. The paper adopts computational grounded theory approach to analyse comments on nostalgic videos, noting that the viewers’ information experiences of video-based nostalgia remain underexplored. It aims to identify nostalgic elements in viewers’ comments on nostalgic videos, and to uncover the underlying sociocultural attributes. Method. Comments were collected from Bilibili videos tagged ‘nostalgia/Chinese retro’ that met view and comment thresholds, yielding 15,734 cleaned comments. Nelson’s computational grounded theory method was applied, integrating BERTopic modeling (silhouette score = 0.55) with iterative human coding by trained coders. Analysis. BERTopic generated 67 topics and hierarchical clustering supported human coders. Coders reviewed representative comments for each topic, conducted independent coding, and adjudicated discrepancies through comparison and discussion. Results. Five dimensions of nostalgic information experiences emerged: Dates, Relations, Events, Artifacts, and Milieus. Building upon this, the paper preliminarily developed the DREAM framework. At the sociocultural level, comments revealed the collective memory reproduction, everyday life emotional traces, and reflections on current society. Conclusion(s). This study provides an initial framework for analysing nostalgic elements in nostalgic video comments and demonstrates the integration of computational and qualitative approaches. Future work will model the mechanisms of nostalgic information experiences in HCI contexts and propose insights for user experience design.
Copyright (c) 2026 Jinhao Li , Yuxiang (Chris) Zhao , Dawei Wu , Qinghua Zhu https://creativecommons.org/licenses/by-nc/4.0
From empathy to exclusion: how Immigrant groups are framed in online discourse
Introduction. When examining moral foundations in immigration discourse on social media, most studies focus on ideology-based groups rather than across specific immigrant groups. This ignores moral framings that depict some communities with empathy and others as threats. This research explores how moral foundations vary in Twitter conversations about five immigrant groups. Method. Tweets were sorted into five categories (based on immigrant groups being discussed: African, Asian, European, Latin American, or Middle Eastern) utilising keyword searches and AI LLM modeling. GPT-3.5 Turbo was employed and achieved a satisfactory performance (0.83) compared to manual human labeling. Analysis. Scores for foundation variables (care/harm, fairness/cheating, loyalty/betrayal, authority/subversion, and purity/sanctity) were analysed using enhMFD1 dictionary. One-way ANOVA tested overall differences between groups and Tukey’s HSD post-hoc test identified specific patterns. Results. Latin American immigrant discourse emphasised care and authority. European-focused tweets featured stronger loyalty. African immigrant discourse highlighted loyalty with moderate authority, discourse about Middle Eastern immigrants showed elevated harm and betrayal, and Asian immigrant discourse portrayed higher fairness-vice. Conclusion(s). Immigrant groups are framed differently through moral language in social media conversations, which may influence perceptions and can inform strategies for addressing harmful narratives on social media.
Copyright (c) 2026 Kirin Mohile , Yiqi Li https://creativecommons.org/licenses/by-nc/4.0
The measurement and influence factors of social consensus in the context of public events
Introduction. This study examines the formation of social consensus during public events by introducing measurable indicators and identifying key influencing factors. Method. Social consensus was defined and measured in terms of its breadth and strength. Factors influencing the formation of social consensus was identified. The SHAP interpretation method was applied to analyse key drivers of social consensus formation, followed by a configuration analysis of core influencing factors using fsQCA to identify the configuration path to achieve consensus. Analysis. A dataset of 155,740 posts was collected from Weibo. Four machine learning regression models were trained and evaluated. The best-performing model was further interpreted using SHAP to identify factors’ contributions. FsQCA revealed three distinct pathways to high consensus and two pathways to low consensus. Results. Consensus is negatively associated with the proportion of individuals with higher education, age difference, and the proportion of individuals with firm opinions, while positively associated with social network structure similarity. Groups that achieve high consensus levels have three key characteristics. Conclusion(s). The study provides a systematic framework for quantifying and analysing social consensus in public events. The findings clarify both consistent predictors and context-specific mechanisms, offering practical insights for guiding public opinion and managing polarization during crises.
Copyright (c) 2026 Ruiyang Chen, Lu An, Yajing Zheng, Gang Li, Chuanming Yu https://creativecommons.org/licenses/by-nc/4.0
Battle of the voices: the effects of inconsistent sentiment valence between video content and danmaku
Introduction. This paper aims to examine the effects of inconsistent sentiment valence between video content and danmaku (positive video content with negative danmaku (PVND) versus negative video content with positive danmaku (NVPD)) and the gender of users (male versus female) on decision-making. Method. An online experiment was conducted. Participants were randomly assigned to one of two experimental conditions (PVND versus NVPD). Analysis. Three hypotheses were tested using two-way ANOVA within SPSS software. Results. Empirical results (N = 224) show significant difference in decision-making between users exposed to PVND and NVPD, but no gender difference is found. In addition, the interaction between inconsistent sentiment valence and gender affects their decision-making. Conclusion(s). This study enriches the literature by not only shedding light on the effects of inconsistent sentiment valence in the dynamic video-based reviews but also adding to the scholarly understanding of gender differences in users’ responses to online reviews.
Copyright (c) 2026 Alton Y.K. Chua , Jiayu Han https://creativecommons.org/licenses/by-nc/4.0
Cultural memory in the digital sphere: reproducing and localising American sitcoms on RedNote
Introduction. Social media are crucial sites for cross-cultural communication and memory construction. On the Chinese social media platform RedNote (Xiaohongshu), vibrant discussions about classic American sitcoms create a unique space for cross-cultural memory. We examine how Chinese fans reproduce and localise these sitcoms, transforming them from imported media into culturally resonant resources. Method. Drawing on digital ethnography and semi-structured interviews, we investigate how fans reshape the cultural memory of these shows and contribute to their localisation. Analysis. Through thematic analysis, we reveal a four-dimensional framework of these memory practices: memory as a toolbox, as play, as identity, and as critique. Results. Our findings show a dynamic progression of fan engagement. Fans initially approach the sitcoms utilitarianly, applying content to their daily lives. This evolves into playful and creative localisation, ultimately culminating in a deep integration of the shows with their personal identities, fostering critical reflection. Conclusion(s). We argue that, far from being passive consumers, Chinese fans actively rework American sitcoms into a versatile collection of cultural resources. Ultimately, it underscores the agency, practicality, and creativity that characterize cross-cultural memory practices in the digital age.
Copyright (c) 2026 Sijia Lu, Yunyi Hu https://creativecommons.org/licenses/by-nc/4.0
Divulgación científica profesionalizada en YouTube: el caso de SciTube
Introducción. Este estudio caracteriza la producción de vídeos de divulgación científica publicados por la empresa SciTube, que combina producción audiovisual profesional con validación académica. Operando como canal público de divulgación y servicio de comunicación científica, convirtiéndola en un caso relevante para analizar estrategias profesionales en YouTube. Método. Se diseñó un análisis mixto basado en 33 variables cuantitativas y cualitativas, organizadas en seis dimensiones. Los metadatos de los 411 vídeos publicados entre 2019 y 2025 se obtuvieron mediante la API de YouTube, mientras que las variables narrativas, visuales, sonoras y de accesibilidad se analizaron mediante observación directa de 50 vídeos recientes. Análisis. Se realizó un análisis estadístico descriptivo de los metadatos y un análisis de contenido sistemático de los vídeos seleccionados para identificar patrones de producción y estrategias narrativas asociadas a mayor rendimiento y engagement. Resultados. Se observa un crecimiento continuo, con una duración media cercana a cuatro minutos y una concentración temática en Medicina y Salud (45,5%). El contenido divulgativo, el tono urgente y la voz femenina se asocian con mayor engagement. Conclusiones. SciTube ha consolidado un modelo profesionalizado de divulgación científica en YouTube, eficaz en términos narrativos
Copyright (c) 2026 Cristina I. Font-Julián , Alejandro Rodríguez-Rodríguez , Enrique Orduña-Malea https://creativecommons.org/licenses/by-nc/4.0
Evaluating the professional competency of university librarians in the digital intelligence era: a survey from China
Introduction. In the digital intelligence era, university libraries are confronted with multiple challenges of an urgent need for transformation and upgrading, a decrease in the number of personnel, and a reduction in funding. Under these circumstances, librarians must possess strong professional competency to drive the development of university libraries. Method. This study employed literature research, network research, and the Delphi method to construct a professional competency model for university librarians in the digital intelligence era, which comprises four 4 dimensions, including comprehensive knowledge, digital intelligence skills, professional skills, and comprehensive thinking, with 19 indicators. Analysis. Based on the competency model, librarians' professional competency levels were dually evaluated from self-evaluation by librarians and evaluation by users. Results. The results reveal that university librarians demonstrate robust capabilities in information management, resource management and application of digital intelligence products, but significantly weak in areas such as information technology knowledge, intelligent service capability, data management capability, and forefront planning capability. Factors such as academic background, job position, usage of digital tools, and configuration of smart devices within libraries can influence librarians' professional competency. Similarly, users' academic background and usage of library resources and services also affect their evaluations of librarians' professional competency.
Copyright (c) 2026 Chuanyu Zhu , Qingqing Ye , Yi Chen , Chuanfu Chen https://creativecommons.org/licenses/by-nc/4.0
Beyond technical performance: Preliminary findings on algorithm aversion in digital library environments
Introduction. This study examines algorithm aversion in digital library contexts, where users increasingly encounter algorithm-enabled services. Prior research in healthcare and finance shows that users often resist algorithmic systems even when they outperform human alternatives, yet little is known about how this phenomenon manifests in the digital libraries context. Method. As part of an ongoing project, we conducted semi-structured interviews with 18 users from two Chinese universities. Participants were selected through theoretical sampling. Interviews were analysed using constructivist grounded theory. Analysis. Open and axial coding of the first 18 interviews produced 42 initial concepts organised into 16 categories under five dimensions: algorithmic, platform, individual, task, and cognitive factors. Results. Preliminary findings suggest that algorithm aversion in digital libraries is multidimensional. Users reported concerns about inaccurate or irrelevant results, cumbersome interfaces, lack of familiarity, and limited trust in recommendations. These patterns suggest that aversion is shaped by both technical shortcomings and user-level factors, leading to frustration, avoidance, and reliance on manual methods. Conclusion(s). These early insights extend algorithm aversion research into a complex service environment, offering evidence that resistance arises from the interplay of technical, individual, and contextual conditions. The ongoing study will expand the dataset and employ DEMATEL to identify causal relationships among factors.
Copyright (c) 2026 Hengyi Fu , Fenfang Cao https://creativecommons.org/licenses/by-nc/4.0
Mapping the evidence-based landscape in Chinese library and information science: a mixed-methods assessment
Introduction. This study systematically explores the thematic distribution, evolutionary trajectory, and future directions of evidence-based research in the Library and Information Science (LIS) discipline in China. Method. A mixed-method design was employed, combining quantitative and qualitative approaches. Data were collected from 18 core CSSCI LIS journals (1999–2025). Methods included word frequency analysis, LDA topic modelling, and qualitative content analysis, with independent coding by two researchers to ensure reliability. Analysis. Thematic and evolutionary analysis was conducted using LDA topic modelling at an optimal k=9, evaluated through perplexity and coherence metrics. Content analysis was performed to identify application dimensions of evidence-based systems in LIS research. Results. The study identifies nine major research topics and reveals a clear shift from traditional, resource-centered themes to strategic, intelligence-aided, and application-oriented research. Evidence-based systems function through five key dimensions: perspective introduction, theoretical support, methodological innovation, diverse evidence integration and expansion of application scenarios. Conclusion. Evidence-based research in Chinese LIS has evolved significantly, showing strong local adaptation and interdisciplinary integration. To enhance future development, it is essential to develop a more comprehensive understanding of evidence-based research, give higher-level attention to evidence-based research, and explore wider horizons and application spaces for its implementation.
Copyright (c) 2026 Junling Ye, Xinyu Chen, Siqi Jiang, Yikun Xia https://creativecommons.org/licenses/by-nc/4.0
Mapping research impact services in health sciences and medical libraries: an observational study
Introduction. Research impact service is an emerging area of library practice responding to rising demand from funding agencies and institutional administration. This study examines the scope of this service in medical and health sciences libraries and informs practice for developing or expanding such initiatives. Method. An observational content analysis was conducted on publicly accessible webpages of member libraries of the Association of Academic Health Sciences Libraries (AAHSL). Libraries were categorized into four service levels, from basic guides (Level 1) to dedicated teams (Level 4). Data were manually collected and descriptively analyzed for service scope, staffing models, tools, metrics, frameworks, and deliverables. Results. Of 189 libraries (174 U.S., 5 Canada, 10 elsewhere), 140 offer research impact services: 49 at Level 1, 61 at Level 2, 16 at Level 3, and 13 at Level 4. Scopus and Web of Science were most frequently used. The San Francisco Declaration on Research Assessment (DORA) and the Leiden Manifesto were most referenced. Conclusion(s). While most libraries offer research impact services, fewer than 20% provide advanced support (Levels 3–4), highlighting the need to strengthen workforce capacity in this area.
Copyright (c) 2026 Xinyu Peng , Fei Yu https://creativecommons.org/licenses/by-nc/4.0
Towards AI for science: developing a conceptual basis for transforming research support services in university libraries
Introduction. This paper reports on an ongoing research project that investigates the development of research support services (RSS) in China’s university libraries to facilitate AI for science (AI4S) projects. Specifically, this paper focuses on developing a conceptual model based on a literature review. Method. A systematic literature review approach was adopted. English and Chinese academic databases were searched. Analysis. After screening, 67 articles were analysed using a thematic analysis and qualitative coding. Results. The analysis points to a conceptual model that consists of 21 library RSS and five main themes: promoting AI readiness, formulating research ideas, building collaborative networks, conducting research, and publishing results. Conclusion(s). Preparing university libraries for AI4S is difficult, facing two primary challenges: (1) the paradigm of AI4S is fast-growing, has not fully emerged; (2) libraries are late and slow in adopting AI technologies. For future studies, the conceptual model can serve as a theoretical basis.
Copyright (c) 2026 Lihong Zhou, Hanyu Miao, Tim Zijlstra, Zengmin Wang https://creativecommons.org/licenses/by-nc/4.0
Bridging the gap between science and society: Mapping libraries' strategies for engaging in the research impact process through semantic analysis
Introduction. Scientific research's societal impact increasingly relies on knowledge dissemination beyond academia. Libraries are evolving from repositories into dynamic intermediaries that bridge societal gaps by enhancing digital literacy and ensuring equitable information access. Existing literature, however, has largely overlooked such institutional intermediaries, limiting systematic understanding of their strategies. Method. We analysed 465 library participation cases from the Research Excellence Framework using a hybrid approach combining large language models (LLMs) and BERTopic semantic analysis. Results. Five key strategies were identified: media communication and public engagement; public dialogue and cultural presentation; artistic collaboration and live experiences; digital content creation and dissemination; and large-scale event coordination. Library contributions are concentrated in Arts and Humanities (76%), primarily within cultural (67%) and societal (22%) impact domains. Conclusion. This study proposes an evidence-based framework elucidating the role of libraries within the research ecosystem, offering practical insights to support the societal translation of research outcomes. Future research should explore differentiated strategies for various library types and the feasibility of generalising these findings to other regions.
Copyright (c) 2026 Wang Zuorong, Sun Jiaxuan, He Shan, Deng Sanhong, Wang Hao https://creativecommons.org/licenses/by-nc/4.0
From human to AI: University students’ trust in generative AI as reference librarians
Introduction. We report an investigation to compare students’ trust in GAI versus human librarians in the scenario of university libraries’ reference services and explore factors affecting students’ trust in GAI. Method. A within-subject design experiment with five tasks covering five disciplines was carried out based on a research model of antecedents for trust in AI, including AI (trustee) characteristics, human (trustor) characteristics, and decision situation (context) characteristics. Two versions of feedback (ChatGPT versus human) were generated for each task and randomly presented to participants without indicating feedback providers’ identities. Analysis. Quantitative analyses were carried out on the data of 146 participants, including descriptive statistics and reliability tests, bivariate correlations, and hierarchical multiple linear regression. Results. Students’ trust in GAI versus human librarians shows no significant difference. AI characteristics emerged as the strongest predictors for students’ trust in GAI as reference librarians, especially the perceived knowledge of AI. Human and decision situation characteristics have limited effects on students’ trust in GAI. Conclusion. The findings refine AI trust antecedents, emphasising system-centric factors over user-centric ones. It supports a shift toward designing ‘trustworthy by design’ AI systems and prioritises verifiable knowledge bases and clarified knowledge presentation ability in developing GAI-embedded reference service systems.
Copyright (c) 2026 Di Wang , Xizhou Deng , Xinyu Lu , Jianting Guo https://creativecommons.org/licenses/by-nc/4.0
Legal deposit libraries’ contribution to the Sustainable Development Goals
Introduction. All types of libraries have a key role to play within the sustainability agenda. This paper mapped the main activities of legal deposit libraries in the UK to the United Nations Sustainable Development Goals (SDGs) to reveal how these libraries contribute to the sustainability agenda. Method. A list of activities of legal deposit libraries was defined from a review of the literature. A mapping exercise was carried out to align these activities with corresponding SDG targets using the global indicator framework. Analysis. Activities with direct and indirect contributions were identified and simple quantitative analysis reported on the extent to which legal deposit libraries help meet the goals and targets. Results. The data shows that legal deposit libraries contribute directly to 12 of the goals, through 18 targets. They contribute indirectly to all 17 goals, through 71 targets. Overall LDLs relate to 89 specific targets, supporting progress in 53% of the targets and 100% of the goals. Conclusion. Legal deposit libraries contribute significantly to the SDGs, mostly through providing access to data, information, and resources, through supporting research, and preserving culture and knowledge.
Copyright (c) 2026 Ellie Jack , Gobinda Chowdhury https://creativecommons.org/licenses/by-nc/4.0
University libraries in transition: Understanding challenges and dilemmas of service transformation in the AI era
Introduction. With the rapid development of artificial intelligence (AI), university libraries are caught in a dilemma between transformation and maintaining the status quo. While the latter is reasonable, the transformation is considered imperative but multidimensionally challenging. Method. By employing a meta-analysis qualitative approach, interview data of 16 librarians and 24 researchers from 2 case studies were analysed to identify the challenges of the transformation in university library services. Analysis. Adopting the actor network theory (ANT) as a basic framework, the thematic analysis reveals the challenges from 5 nonhuman actors and 4 human actors (including policies, finance, infrastructure and software, AI algorithms, ethics, administration, library, database agents, and users). Results. The inductive coding analysis identified 28 challenges of university library services transformation. Based on the findings, this study proposed a model of conflict among actors. Conclusion(s). The identified challenges provide useful theoretical and practical evidence for optimising AI-driven transformation of university libraries. Moreover, the case setting is based in China, but the findings offer useful insights and indications that can be shared across international borders.
Copyright (c) 2026 Hanyu Miao , Zengmin Wang , Lihong Zhou https://creativecommons.org/licenses/by-nc/4.0
The impact of AI on librarians' profession: Chinese librarians' perceptions and concerns
Introduction. The application scope of artificial intelligence (AI) in libraries is gradually expanding, inevitably exerting certain influences on librarians. An investigation on librarians' perceptions of AI application within libraries, as well as librarians' AI literacy and AI-related training programs for librarians provided by libraries has significant management and development implications. Method. An online questionnaire comprising 4 5-point Likert scales of total 15 items was distributed to randomly selected Chinese librarians. 392 valid responses were collected, and descriptive statistical analysis was conducted using SPSS 26.0. Results. Under the context of AI applied in libraries, librarians hold a more positive attitude towards AI, perceiving support effect higher than substitution effect on profession. However, contradictions and concerns of inadequate application depth of AI in libraries, low level of librarians' AI literacy, insufficient AI-related training programs for librarians, and future employment concerns caused by the development trend of AI exist. Conclusion. Librarians' perceptions and concerns regarding AI application provide references for personnel management in libraries and professional development of librarians, bringing the necessity of firmly believing the irreplaceable core role of library professionals in human-machine collaboration.
Copyright (c) 2026 Yi Chen , Qingqing Ye , Shiyi Xiao , Zike Jiang https://creativecommons.org/licenses/by-nc/4.0
Estrategias nacionales frente a la soledad no deseada (SND) y bibliotecas: un análisis preliminar en el entorno de la OCDE (National strategies against unwanted loneliness and libraries: a preliminary analysis within the OECD context)
Introduction. Unwanted loneliness has become a key issue in debates on social health, with significant economic and health implications. Several governments have begun to develop national strategies and design targeted policies to reduce it. This study provides a comparative overview of these strategies across OECD countries, emphasizing the importance of community infrastructures—particularly public libraries—in mitigating social isolation. Method. An exploratory review (scoping review) was conducted of loneliness-related policies in the 38 OECD member countries, identifying seven national strategies. The study followed the PRISMA 2020 protocol (Page et al., 2021). A coding matrix was applied to evaluate the presence and role of libraries in each strategy. Analysis. The strategies were examined according to their level of institutional development and funding, as well as the recognition and role of libraries, considering their presence, visibility, and degree of involvement. Results. The findings reveal uneven institutionalization of loneliness as a public policy issue. Public libraries are present—explicitly or implicitly—in six strategies, though their participation varies widely, ranging from symbolic mentions to programmatic recognition. Conclusion. Unwanted loneliness emerges as a new field of public action and an opportunity for libraries to strengthen their role as social infrastructures in its prevention.
Copyright (c) 2026 Sara Martínez Cardama , Ana Reyes Pacios https://creativecommons.org/licenses/by-nc/4.0
Requalificação participativa de uma biblioteca da Universidade Estadual Paulista como centro de recursos para a aprendizagem e pesquisa: um estudo de caso
Introduction. Presents and analyzes the requalification process carried out between 2021 and 2024 at the library of São Paulo State University (UNESP) in São João da Boa Vista, Brazil, which aimed to create environments within the library and begin its transformation into a Learning and Research Resource Center (CRAI) through a redevelopment project. Method. A case study approach was adopted, contextualized through a theoretical framework developed from bibliographic research and analyzed in light of data obtained from forms and documentation, quantitatively and qualitatively. Analysis. Highlights the fact that the process was led by a professional librarian and the participation of the community throughout it. Points out that the project addressed the SDGs and was developed using a co-design methodology. Results. The creation of environments within the library and the implementation of media resources concurrently with the project implantation added value to the CRAI initiative in terms of innovation and digital transformation. This led to a redefinition of the library's spaces and dynamics, enhancing users’ information and media literacy and fostering greater autonomy. Conclusions. The project successfully met its primary objectives: creating suitable environments in the library and establishing it as a CRAI, aligned with contemporary trends and an innovation-driven context.
Copyright (c) 2026 João Pedro Alves Cardoso https://creativecommons.org/licenses/by-nc/4.0
Bridging the prehospital communication gap: evaluating a smart glass-enabled telemedicine system
Introduction. Accurate and timely communication between emergency medical services (EMS) providers and remote physicians is vital for high-quality prehospital care, yet traditional phone or radio systems often fail to convey sufficient contextual information. Smart glasses offer a promising alternative by enabling real-time, first-person video and data sharing. This study evaluates a smart glass-based telemedicine system to understand how it is used in practice and perceived by emergency care providers. Method. We conducted 16 near-realistic simulation-based evaluations involving EMS providers and emergency physicians. We analysed the system usage and user experience through multiple approaches, including video analysis, eye-tracking, interviews, and surveys. Results. The smart glass-based telemedicine system was positively received by EMS and physician participants, who praised its effectiveness in enhancing communication and its ease of use. However, observations of actual usage—such as longer physician connection times and interaction challenges with the device—along with broader sociotechnical issues including infrastructure readiness, workflow integration, and ergonomic concerns, highlight the need for more thoughtful design to support successful adoption and deployment at scale. Conclusion. Smart glasses hold significant promise for augmenting prehospital communication, but successful adoption will require careful integration into EMS workflows, ergonomic design refinements, and resilient technical infrastructure.
Copyright (c) 2026 Enze Bai, Zhan Zhang, Yincao Xu, Kathleen Adelgais, Mustafa Ozkaynak https://creativecommons.org/licenses/by-nc/4.0
Suggestions regarding the relationship between daily information-seeking habits and the formation of ageism
Introduction. Various previous studies have suggested a relationship between information-seeking preferences and ageism. However, the mechanisms and processes underlying the relationship between information preference and ageism have not been explored. Moreover, both of the aforementioned studies assumed the provision of accurate information and knowledge. Therefore, this study aimed to determine whether people’s information-seeking preferences affect ageism and to examine the mechanisms underlying this effect. Method. A questionnaire survey was conducted among 154 undergraduate students enrolled at national universities in Japan. Analysis. A covariance structure analysis was conducted to test whether information-seeking preferences affect ageism. Results. The factors of information-seeking preferences were related to ageism. Among the factors of ageism, antilocution and discrimination were particularly affected. Conclusion(s). While the Internet facilitates interaction with people of different generations and values, it has also been suggested that information-seeking preferences can reinforce ideological inclinations. This study shows that information-seeking behaviour can inhibit ageism, but also indicates that individuals may be more prone to ageist attitudes when relying on people as information sources.
Copyright (c) 2026 Masaki Takeda; Satoru Suto https://creativecommons.org/licenses/by-nc/4.0
Between reform and reality: institutional logics of data and digital in New Zealand’s health system transformation
Introduction. We report on an investigation into the strategic role of data in improving health equity during Aotearoa New Zealand’s 2019–2025 health reforms, using institutional logics to uncover stakeholder differences and barriers. Method. Semi-structured interviews were conducted with fourteen professionals involved in the strategic use of health data and technology. Participants included government IT/data policy leads, senior IT/data leaders, Māori data governance experts, general practitioners, and IT health industry representatives. Analysis. We identified a framework of eight institutional logics shaping stakeholders’ visions of data ideals: public good/equity logic, bureaucratic logic, market logic, professional logic, innovation logic, indigenous sovereignty logic, liberal-individual rights logic, and national sovereignty logic. Results. Tensions between differing logics surrounding the ideal role of data in system reform help explain implementation challenges. These included balancing individual and collective data sovereignty and contrasting views on ownership of patient data as a public, commercial or professional good. Conclusion(s). Whilst national shared systems have potential to increase equity through improved data flow, key implementation issues can be explained by a legacy of health data power struggles embedded in different institutional logics, intensified by fragmentation and underinvestment. Adaptive governance is needed to balance logics in delivering the vision for transformation.
Copyright (c) 2026 Lesley Middleton, Jocelyn Cranefield, Verna Smith https://creativecommons.org/licenses/by-nc/4.0
Dynamic complexity adaptation: how LLMs enhance medication information literacy
Introduction. This study investigates how large language models (LLMs) enhance medication information literacy through dynamic complexity adaptation. Addressing global medication safety challenges exacerbated by low literacy, we evaluate whether LLM-generated content surpasses human community answers in reliability while balancing professionalism and accessibility. Method. Using multi-source medical Q&A datasets (184,843 entries), we curated 1,229 medication literacy-focused units (4,916 entries) assessed via the standardised MedLitRxSE scale. Double-blind scoring (κ=0.82) and ANOVA compared three LLM complexity variants against baseline answers. Results. Professionally calibrated LLM content (Variant 5) significantly outperformed human- generated answers across 78.6% of literacy metrics (p<0.001), excelling in risk communication (+30%) and operational knowledge (+17%). A ‘golden interval’ for optimal comprehension was identified at terminology density (15–25%) and dependency distance (3–4 words). Conversely, oversimplified content (Variant 1) reduced dose accuracy and increased ethical risks by 62.3%. Conclusion(s). LLMs elevate medication literacy through risk-stratified complexity adaptation: high-risk scenarios (e.g., dosing) demand uncompromised precision (Variant 5), while lower- stakes contexts (e.g., storage) tolerate simplification (Variant 1). This framework resolves the readability paradox, proving accessibility requires professional accuracy. Future work must expand into multilingual validation and hybrid generation strategies.
Copyright (c) 2026 Tan Fu , Wen Lou https://creativecommons.org/licenses/by-nc/4.0
Her cycle, its logic: Information practices and gendered governance in MCT apps
Introduction. This study examines menstrual cycle tracking (MCT) apps as information systems that organise bodily knowledge, highlighting tensions of empowerment, discipline and information justice. Method. Data included 1,300 Douyin comments mined on 10 June 2025 and 15 semi-structured interviews conducted from June to August 2025. Comments were clustered, modelled and sentiment-analysed; interviews were anonymised and coded through directed content analysis. Analysis. Quantitative techniques identified thematic patterns and sentiment distributions in user comments, while qualitative coding yielded axial categories: technological dependence, data discipline, fragile trust, privacy illusion, gendered presumptions and everyday resistance. Results. Apps enhanced bodily awareness but reinforced algorithmic optimisation, reproductive defaults and commercial opacity. Users moved between reliance and resistance, experiencing empowerment and regulation simultaneously. Conclusion(s). MCT apps illustrate how information systems discipline under the guise of care. Justice-oriented practices such as participatory design, transparent governance and inclusive infrastructures are needed to reframe FemTech as a space of equity and information fairness.
Copyright (c) 2026 Yanli Zhou, Yunjie Tang https://creativecommons.org/licenses/by-nc/4.0
Understanding credibility: toward a networked evidence model of health information
Introduction. Severe health issues trigger urgent information needs, yet digital environments complicate judgments of what counts as credible evidence. Traditional authority rooted in medical expertise now intersects with peer testimony, platform structures, and algorithmic curation. Method. We analysed qualitative interviews with 23 parents whose children contracted COVID-19, extending Uncertainty in Illness Theory (UIT) by reinterpreting the concept of ‘credible authority’ through a new theoretical lens. Analysis. Using an abductive, theory-building approach and a crystallisation immersion method, we examined how parents enacted epistemic practices in digital health contexts. Results. We propose the networked evidence model (NEM), which shows that health information is actively organised, validated, circulated, and trusted within socio-technical systems. Evidence was shaped through alignment across institutional expertise, testimonial resonance, and platform signals. Conclusion. NEM reframes credible authority as a networked accomplishment, advancing information science and informing the design of systems that promote equitable, transparent, and trustworthy access to health knowledge.
Copyright (c) 2026 Karen Joy, Tawfiq Ammari https://creativecommons.org/licenses/by-nc/4.0
Towards a typology of epistemic relationships in human–AI interaction
Introduction. This study investigates how academics negotiate epistemic relationships (ERs) with artificial intelligence (AI) in research and teaching. We conceptualize ERs as the positioning of humans and AI in relation to knowledge, asking: What epistemic relationships emerge in researchers’ interactions with AI, and how are they enacted across academic knowledge practices? Method. Semi-structured interviews were conducted in two independently collected datasets with 31 academics across regions and disciplines. Analysis. We developed a five-dimensional codebook including three epistemic attributes (assessment perspective, trust type, human epistemic status) and two analytic devices (activities and metaphors). We refined the coding through iterative analysis and identified recurring patterns across participants’ accounts in both datasets. Results. Five recognizable ER types emerged: Epistemic Abstention, Instrumental Reliance, Contingent Delegation, Co-agency Collaboration, and Authority Displacement. These types reflect variations in how participants assess and trust AI, position themselves epistemically, and embed AI in academic activities. Conclusion(s). Our study contributes to conversations on information literacies and the ethical use of AI. We highlight the contingent and practice-dependent nature of ERs, suggesting a shift beyond static metaphors of AI toward a more nuanced account that captures the epistemic dimensions of human–AI knowledge co-construction.
Copyright (c) 2026 Shengnan Yang, Rongqian Ma https://creativecommons.org/licenses/by-nc/4.0
Understanding user behaviors and satisfaction in LLM-assisted tasks: prompting strategies and user knowledge states among college students
Introduction. This study examines how users interact with large language models (LLMs), focusing on the interplay between users’ knowledge states and prompt strategies in shaping satisfaction. Method. Data were collected from 39 students, yielding 187 valid task records. Participants reported knowledge states and satisfaction and submitted dialogues for analysis. Prompt strategies and the character of LLM were coded, and a strategy matching rate was proposed as a novel indicator of LLM application ability. Analysis. Analyses combined descriptive statistics, correlation analyses, Mann–Whitney U tests, and mixed-effects logistic regression, with intercoder reliability established through iterative agreement. Results. Directive, contextual, and iterative refinement strategies were most frequently observed, with notable discrepancies between self-reported and coded strategy use. Regression analyses showed that non-delegability and creativity increased the likelihood of satisfaction exceeding expectations, while topic familiarity and knowledge status effects reduced it. Chain-of-thought and self-consistency strategies positively predicted satisfaction, whereas directive and role prompting strategies had negative effects. Conclusion(s). Satisfaction in LLM-assisted tasks emerges from the interaction of users’ knowledge states, task characteristics, and prompting strategies. By introducing strategy matching rate as an empirical indicator of LLM application ability, this study contributes a practical approach to assessing AI literacy and advances understanding of human–LLM collaboration.
Copyright (c) 2026 Tzu-Yun Chien, Po-Yu Chen, Muh-Chyun Tang https://creativecommons.org/licenses/by-nc/4.0
Collaborating with large language models in literature screening for a systematic review of college students’ GenAI literacy
Introduction. Literature screening is among the most time- and labour-intensive phases of systematic literature reviews (SLRs). Although large language models (LLMs) have been explored for screening, prior work has focused on medical and environmental domains and mainly benchmarked LLMs against human coders, offering limited guidance on collaborative integration in SLRs. Method. This study evaluated 12 GPT model–prompt configurations in an SLR of 1,616 publications. Two human coders screened a 10% sample (n = 162) to create a gold standard for model comparison. Performance was assessed using balanced accuracy, recall for inclusion, time efficiency, and cost efficiency. Disagreements between humans and models were analysed. Analysis. Bootstrap tests compared performance across configurations. Open coding identified error types in human–model disagreements. Group discussion resolved discrepancies. Results. GPT-5 Zeroshot and GPT-4o-mini Fewshot achieved the highest performance (accuracy = 0.990 and 0.946; recall = 1.000 and 0.933). GPT-4o-mini was faster and cheaper but more prone to overly rigid rule application. Error analysis identified 10 mismatches, leading to two corrections of human miscoding. Conclusion. LLM-assisted screening can reduce workload, improve efficiency, and correct human errors in SLR. Practical guidelines for prompt design and confidence thresholds can position LLMs as collaborative tools in SLRs.
Copyright (c) 2026 Wonchan Choi , Joyce Lee , Besiki Stvilia , Yan Zhang , Hyerin Bak https://creativecommons.org/licenses/by-nc/4.0
A comparison of human and ChatGPT classification performance on complex social media data
Introduction. Generative artificial intelligence tools, like ChatGPT, are an increasingly utilised resource among computational social scientists. Nevertheless, there remains space for improved understanding of the performance of ChatGPT in complex tasks such as classifying and annotating datasets containing nuanced language. Method. In this paper, we measure the performance of GPT-4 on one such task and compare results to human annotators. We investigate ChatGPT versions 3.5, 4, and 4o to examine performance given rapid changes in technological advancement of large language models. We employ a dataset containing human-annotated comments from YouTube and X. We craft four prompt styles as input and evaluate precision, recall, and F1 scores. Analysis. Both quantitative and qualitative evaluations of results demonstrate that while including label definitions in prompts may help performance, overall GPT-4 has difficulty classifying nuanced language. Results. Qualitative analysis reveals four specific findings: 1) cultural euphemisms are too nuanced for GPT-4 to understand, 2) interpreting the type of ’internet speak’ found on social media platforms is a challenge, 3) GPT-4 falters in determining who or what is the target of directed attacks (e.g., the content or the user), and 4) the rationale GPT-4 provides is inconsistent in logic. Conclusion. Our results suggest the use of ChatGPT in classification tasks involving nuanced language should be conducted with prudence
Copyright (c) 2026 Breanna E. Green, Ashley L. Shea, Pengfei Zhao, Drew B. Margolin https://creativecommons.org/licenses/by-nc/4.0
Integration of generative artificial intelligence (GenAI) in metadata training
Introduction. GenAI tools are adopted by information professionals globally, including GenAI incorporation into metadata workflows in archives and libraries. Researchers and practitioners emphasise the critical need for GenAI learning integration into coursework to prepare iSchools graduates for this emerging professional demand. While reports on GenAI content integration in iSchools curricula are increasing, there is a lack of publications about GenAI integration in courses focusing on digital repository metadata. Method. University of North Texas recently integrated GenAI practical metadata learning in an advanced graduate course. This paper describes this integration and reports results of its testing. Analysis. The author performed qualitative and quantitative analyses of practical assignment submissions in which students used GenAI tools for generating metadata records and evaluated the process and outcomes. Results. AI-generated metadata varied in completeness depending on the GenAI tool, its version, and prompt used, while typically lacking accuracy. Students expressed appreciation of this practical experience, reported developing greater confidence in using GenAI tools and understanding their advantages and disadvantages in metadata work, demonstrated development of analytical and troubleshooting skills. Conclusion. This paper is expected to be useful for iSchools metadata educators, researchers, and practitioners.
Copyright (c) 2026 Oksana L. Zavalina https://creativecommons.org/licenses/by-nc/4.0
The dual impact of generative AI on research: structural stability and attention reallocation
Introduction. We present an exploratory analysis of the short-term effects of generative AI (GenAI) on the research landscape. As GenAI becomes more deeply embedded across multiple stages of scientific work, there is an increasing need to examine its broader impact on all forms of research. Method. We retrieved 24,309,359 publications (2020–2024) from OpenAlex across 26 disciplines after excluding records with missing references or unspecified research fields. Distinct research topics were identified via graph clustering algorithms for subsequent analysis. Analysis. Using a multidimensional framework, we calculated topic diversity indices to examine temporal evolution, constructed topic networks to measure structural changes via clustering coefficients, and assessed GenAI publication proportions among hot topics. Results. The available evidence detected no significant changes in overall topic variety or network structural properties from 2020 to 2024. However, within the most prominent topics, GenAI-related publications increased significantly, indicating internal reallocation of research attention. Conclusion. Initial evidence suggests no detectable macro-structural changes coexist with micro-level attention shifts toward GenAI within established domains. This dual pattern suggests that GenAI is less a disruptive force than a catalyst that amplifies research attention within established domains.
Copyright (c) 2026 Xiaoting Xu , Naixuan Zhao , Jiang Li , Xiao Hu https://creativecommons.org/licenses/by-nc/4.0
From search to work tasks: exploring students’ AI chatbot information practices in higher education
Introduction. Research on AI chatbot use in higher education has largely focused on undergraduates, often overlooking graduate students or treating both groups as a single population. Drawing on activity theory, this study examines how task type shapes differences in AI chatbot use among undergraduate and graduate students. Distinguishing task types is theoretically important because shifts in the object of activity shape how students perceive agency, organise information practices, and engage with AI tools. Method. Eighteen students participated in semi-structured interviews. Transcripts were coded in NVivo using activity theory components: Subject, Object, Tools, Rules, Community, Division of Labor, and Outcome. Analysis. A deductive coding approach identified how students engaged with AI tools in relation to different learning tasks. Data triangulation enhanced credibility by combining self-reported reflections with interaction records. Results. Undergraduates primarily used AI for course-related search tasks, often accepting responses with limited verification. Graduate students engaged in more complex work tasks and were more likely to verify AI outputs with secondary sources. Conclusion. Task type influenced students’ information interaction, particularly in credibility judgments and ethical considerations. These findings highlight the importance of task-based distinctions in AI literacy instruction and suggest tailoring guidance to both education level and task context.
Copyright (c) 2026 Bo Hyun Hong https://creativecommons.org/licenses/by-nc/4.0
‘Will there be parmesan?’ – Understanding migrants’ information needs and sources for transition to new country
Introduction. Migration is an information-intensive process—migrants require information throughout the process of their move. Extant literature identifies what information migrants need, how they seek it, and the barriers encountered in new information environments. However, not much work has examined what enables migrants to access information in new environments. Method. To address this gap, a qualitative approach was adopted. Semi-structured interviews were conducted with a cohort of 23 migrants in Victoria, Australia. All participants had moved more than once in their life. Analysis. Following data collection, a thematic analysis approach was adopted. We examined the data for emergent themes. Data was coded by the first author and refined through an iterative process with four co-authors. Results. Data analysis revealed 4 themes and 16 sub-themes. We identified enablers for navigating new information environments: navigating the physical landscape of new country, drawing on local contacts in new country, leveraging online recommender systems in new digital environments, drawing on previous experiences of navigating information environments. Conclusion. Given the findings, we suggest serendipitous information system design can have a supportive effect for migrants navigating new digital information environments. We also indicate the role libraries can play in helping migrants make the digital journey.
Copyright (c) 2026 Rashika Bahl, Shanton Chang, Dana McKay, George Buchanan, Marc Cheong https://creativecommons.org/licenses/by-nc/4.0
Towards automated genre conversion: aggregating thematic events in classical Chinese chronological histories
Introduction. This study explores the automatic restructuring of chronological historical texts into historical narratives. It aims to identify and aggregate dispersed event records to reconstruct macro-narrative structures. Method. We propose a framework combining event extraction and unsupervised clustering. First, an event detection model tailored for classical Chinese is developed. Next, we employ contrastive learning to train a semantic representation model using the thematic text Tongjian Jishi Benmo. Finally, unsupervised clustering aggregates vectorised paragraphs into event-specific groups. A mapping dataset linking the chronological Zizhi Tongjian to thematic chapters was created for quantitative evaluation. Results. Experiments indicate that the contrastive learning model combined with the DBSCAN algorithm yields the best performance, with an adjusted rand index (ARI) of 0.43 and normalised mutual information (NMI) of 0.78. The model successfully aggregates semantically related paragraphs, demonstrating an initial capability to transform chronological annals into event-centered accounts. Conclusions. While precision in event boundaries needs improvement, this research validates the feasibility of automated narrative reconstruction, offering methodological insights for digital historical knowledge organisation.
Copyright (c) 2026 Litao Lin , Shiyan Ou https://creativecommons.org/licenses/by-nc/4.0
Redefining critical literacies and ethics in human–machine conversations in the emergent AI-human zone
Introduction. The ‘Emergent Zone’ is a boundary space where humans and AI co-construct meaning, authorship, and responsibility in response to the transformative impact of conversational information retrieval systems. Method. Develop a conceptual framework by synthesising the information foraging theory, Vygotsky’s Zone of Proximal Development (ZPD), and Kuhlthau’s Zones of Intervention, all grounded in LIS literature and expanded through critical AI perspectives. Analysis. AI’s roles as forager, scaffolder, and intervener are illustrated by illustrative exemplum cases from library references, disinformation detection, and learning environments, revealing both efficiencies and profound challenges to agency and accountability. Results. The framework underscores the urgent need for new critical literacies (e.g., prompt, interpretive, algorithmic, and ethical) and positions meta-literacy as an integrative foundation for LIS. Conclusion. The Emergent Zone advances scholarship on AI–human interaction, calling for new literacies and reimagined pedagogies and ethics in LIS, and proposes future research emphasising justice-oriented and cross-cultural approaches.
Copyright (c) 2026 Anika Meyer ; Marlene Holmner , Theo JD. Bothma https://creativecommons.org/licenses/by-nc/4.0
‘A good question is half the answer:’ a learning-oriented K-12 prompt literacy competency cultivation framework
Introduction. As an emerging key competence, prompt literacy is gradually becoming an essential component of artificial intelligence literacy and is increasingly emphasised in K–12 education. This study aims to construct a learning-oriented K-12 prompt literacy competency cultivation framework. Method. The framework was theoretically informed by Bloom’s taxonomy, Zimmerman’s self-regulated learning theory, and existing AI literacy frameworks for K–12 students. The framework was then refined through the deductive content analysis based on the semi-structured interview data that were conducted with teachers and students. Results. The framework comprises three dimensions. (1) Four core competencies: prompt cognition, prompt skills, prompt thinking, and prompt values; (2) three learning objectives: understand, apply, and evaluate; (3) four cultivation stages: observation, emulation, self-control, and self-regulation. The indicators of competencies, specific descriptions of objectives, and corresponding cultivation approaches were also proposed. Ultimately, a stage-based, progressive, and highly actionable guideline for cultivating prompt literacy was developed, which clearly specifies the competencies to be nurtured and the learning objectives to be achieved at each stage. Conclusion(s). This study contributes to AI literacy education by establishing the first comprehensive framework for prompt literacy cultivation in K–12 students.
Copyright (c) 2026 Jing Zhou , Li Si , Xianrui Liu https://creativecommons.org/licenses/by-nc/4.0
Eudaimonic media engagement in virtual reality: Memory, identity, and well-being among older Black adults
Introduction. While virtual reality (VR) is often studied for entertainment, its role in supporting reflection and well-being in later life is underexplored. This exploratory study investigates how older Black adults use VR to engage with personal history, exploring its potential as a restorative technology. Method. Nine older Black adults who were VR novices engaged with tailored scenarios on an Apple Vision Pro headset. We then conducted semi-structured interviews to explore their reflective experiences. Analysis. Interview transcripts were analysed using a focused thematic analysis guided by theories of eudaimonic engagement and existential resonance. Results. The findings show that VR facilitates existential resonance, where generic scenes align with personal values. This turns passive memories into a participatory reliving of the past, described as being ‘in it, not looking at it.’ These resonant encounters were eudaimonically restorative, transforming bittersweet emotions into peace and joy. Conclusion(s). The study demonstrates that VR can function as a technology of care by facilitating immersive resonance. This process supports restorative reflection with applications in reminiscence therapy and grief support, reframing the medium as a mirror for personal history.
Copyright (c) 2026 Kuo-Ting (Tim) Huang , Yanyun (Mia) Wang https://creativecommons.org/licenses/by-nc/4.0
AI literacy training for K–12 learners: Community-led non-formal education practices in China
Introduction. Artificial intelligence (AI) literacy has become increasingly important in K–12 education, yet its implementation in community-led, non-formal settings remains underexplored. This study examines how community-led AI literacy training for K–12 learners are implemented in non-formal community settings in China, with a specific focus on the motivations and challenges faced by university-student volunteer instructors. Method. Data were collected through semi-structured interviews with eight university-student volunteers serving as instructors and field observations of ten training sessions across five urban communities in summer 2025. Analysis. Interview transcripts were thematically coded and triangulated with observational data, using an adapted version of Detlor et al.’s framework for community-led digital literacy training. Results. Three dimensions—volunteer engagement, learning environments, and program components—shaped AI literacy training program. While volunteers’ intrinsic motivation and disciplinary background facilitated instruction, challenges such as inconsistent funding, limited equipment, and fragmented curricula constrained the perceived effectiveness and sustainability of the training program. Conclusion(s). Community-led initiatives can complement formal schooling in promoting AI literacy, but their sustainability and scalability depend on systematic support, adequate resources, and stronger organisational coordination.
Copyright (c) 2026 Yanke Zhao , Xiao Hu , Yuxiang (Chris) Zhao, Shijie Song , Jinhao Li https://creativecommons.org/licenses/by-nc/4.0
Local news at a distance: psychological distance and the formation of news deserts
Introduction. News deserts, geographic areas with little local news or news organisations, pose challenges to democratic processes. However, individuals’ attention to news may vary depending on how much they care about local matters. As an initial exploration of these dynamics, this paper proposes a framework that links news deserts to psychological distance through Construal Level Theory (CLT). Method. This study conducts (a) the literature review focused on news deserts and CLT and (b) case studies of city co-mentions in news to develop the framework that considers both symbolic and physical aspects of local news. Analysis. City co-mention network analysis illustrates how news can reduce psychological distance by make them feel close, whereas news deserts expand distance, rendering issues more abstract. Results. News deserts emerge not only from the absence of news organisations but also from a psychological void, in which weak or missing linkages isolate places and diminish residents’ engagement with them. Our case study of crime and sports news demonstrates contrasting effects of psychological distance on news attention. Conclusion. Linking news deserts to psychological distance opens new research opportunities: measuring psychological distance, reconceptualising news deserts psychologically, and connecting news to audience perceptions.
Copyright (c) 2026 Tugce Burcu Gundogdu , Jieshu Wang , Brian S. Butler , Myeong Lee https://creativecommons.org/licenses/by-nc/4.0
Transparency as organizational accomplishment: How an astronomical collaboration learns to observe its algorithms
Introduction. Recent work on algorithmic systems has characterized such systems as relational entities, which are embedded in larger sociotechnical assemblages. We examine some implications of this framing for the practical accomplishment of transparency by organizations and communities. Specifically, we investigate a large astronomical survey project’s effort to render its observation scheduling algorithm transparent to a large international community of researchers. Method. We report on one part of a larger ethnographic study with the survey project, using interview data and documentary data as the primary empirical sources for this analysis. Analysis. The authors conducted theory-generative qualitative coding based on grounded theory methodology, developing three codes relevant to the organizational accomplishment of transparency in this case. Results. We argue that from the perspective of an organized group that is wrestling with the opacity of its algorithmic systems, accomplishing transparency is effortful in design and organizing work, it is ongoing, and it produces novel organizational relations. Conclusions. Relational conceptions of algorithmic and AI/ML systems highlight the work and challenges of accomplishing transparency beyond processes of publication, visibility, or access. Greater attention to this organizing work is warranted in the broadening rollout of such systems in scientific and social life.
Copyright (c) 2026 Will Sutherland, Anissa Tanweer https://creativecommons.org/licenses/by-nc/4.0
Voices from the river: exploring digitally inclusive tools with marginalised fishing communities in Bangladesh
Introduction. This study investigates how small-scale fishing communities in Bangladesh, often excluded from digital initiatives, articulate their priorities for inclusive tools. Using digital inclusion and intersectionality frameworks, it examines how gender, age, and livelihood contexts shape digital aspirations. Method. Sixteen participatory ideation workshops were conducted in two districts with 128 participants stratified by age and gender (elderly men, elderly women, young men, young women). Sessions involved community mapping, problem identification, persona-building, and co-design of digital futures. Data were transcribed, translated, and thematically analysed, guided by Jia et al.’s five-dimensional digital inclusion model. Analysis. Thematic coding and intersectional comparison revealed both shared priorities and subgroup-specific visions. Findings were aligned with digital inclusion and participatory design literature to identify theoretical and practical implications. Results. Across all groups, participants emphasised accessible tools for livelihoods, regulation, and service access. Gendered differences emerged, with men prioritising occupational and market-based tools, and women focusing on caregiving, health, and small-scale entrepreneurship. Generational divides also shaped digital imaginaries, with older participants seeking stability and safety, while youth highlighted skills, autonomy, and transformation. Conclusion. Digital inclusion is a situated, intersectional process requiring participatory, context-sensitive approaches. The study underscores the need to recognise intra-community diversity when designing equitable digital futures.
Copyright (c) 2026 Md Khalid Hossain, Gillian Christina Oliver, Misita Anwar, Tanjila Kanij, Manika Saha https://creativecommons.org/licenses/by-nc/4.0
‘If I could go to one place’: examining city-based information practices from the perspective of city residents
Introduction. This paper examines information as an exchange between city government and city residents. The goal is to better understand residents’ perceptions of interacting with city government and to describe their suggestions for improvement, including centralised information hubs. Method. A qualitative study with 30 city residents in Austin, Texas, U.S.A. includes semi-structured interviews and a member check focus group to explore themes from the information studies and urban studies literature. Analysis. Thematic analysis was used to identify themes in the interview data. Results. Participants express frustration with existing channels for engaging with city government and cite a lack of access to information as a barrier. Participants do not mention open data portals, which cities invest in but are not accessible to those who lack data analysis skills. Participants report that they wish they could go to one place to get information about local issues. Conclusion(s). Participants suggest centralised information hubs as mechanisms that could improve information exchange between city government and residents. Relatedly, investment in open data portals has not solved the problem of resident engagement in local government; indeed, residents do not even bring up the topic. Combining insights from information studies and urban studies can help to address this gap.
Copyright (c) 2026 Chelsea E. McCullough , Kenneth R. Fleischmann https://creativecommons.org/licenses/by-nc/4.0
Changing how we count: the New Zealand census and Māori data
Introduction. This paper examines the New Zealand Government’s 2025 decision to cancel the 2028 census and replace it with administrative data and annual sample surveys. While censuses have supported population measurement and planning, the shift raises concerns for Māori about data quality, under-representation, and Indigenous data sovereignty. The study situates this decision within the history of census practice in Aotearoa New Zealand. Method. The paper adopts a historical and literature-based approach, drawing on census data from 1851 to 2023, government reports, and scholarship on census and administrative data, including Māori and organisational critiques. Analysis. The analysis compares traditional census methods with administrative data models, identifying efficiencies alongside risks of bias and undercounting. It examines Māori participation in the 2013, 2018, and 2023 censuses, limitations of iwi affiliation data, and implications for equitable representation, alongside Māori-led initiatives and international experiences. Results. Findings show that low Māori response rates have produced incomplete data increasingly supplemented by administrative sources that often reinforce inequities. Māori-led partnership models have improved participation and data quality in some rohe, while international evidence confirms risks of undercounting without co-governance. Conclusion. Cancelling the 2028 census risks deepening inequities and undermining Māori data sovereignty, but Māori-led governance offers equitable alternatives.
Copyright (c) 2026 Spencer Lilley https://creativecommons.org/licenses/by-nc/4.0
Proximity in coffee shop culture: exploring the potential of a common ground environment
Introduction. Coffee shops have long provided a unique atmosphere that fosters social connection through informal information-sharing. They can provide common ground spaces that allow for civil discourse where individuals can share diverse perspectives. Physical proximity in a coffee shop culture can result in conceptual proximity that enables discussion of contentious matters. Method. Participant observer analysis of coffee shop engagements and semi-structured interviews with patrons enabled examination of how proximity may afford opportunities for civil discourse even amid conflict in common-ground environments. Analysis. Data was coded inductively, line-by-line, to identify themes. The Bonnici and O’Connor proximity model provided a framework for determining how noise may be reduced in the communication channels to foster common ground environments, enabling free information-sharing and meaningful dialogue in a fractured society. Results. The themes of setting, community, information ground, social connection, and information commons emerged as significant contributors to the proximity patrons experienced within the space, revealing the role of proximity in strengthening weak social ties and deepening patrons’ sense of belonging. Conclusion. Coffee shop culture can provide a setting in which individuals can gather in various numbers and groupings to connect in unlikely and meaningful ways, thus enabling information flow that can break down conceptual barriers.
Copyright (c) 2026 Amy D. Lanier, Brian C. O'Connor https://creativecommons.org/licenses/by-nc/4.0
Reframing data papers as boundary objects: aligning data narratives with reuse-oriented user expectations
Introduction. This study investigates how the narrative structure of data papers, as boundary objects, aligns with the needs of data reusers, focusing on both document structure and reusers’ preferences. Method. Two approaches were employed: (1) a textual analysis of discourse components and data events, and (2) an exploration of reusers’ preferences and perceived use value through interviews. Analysis. A total of 210 data papers were randomly sampled for content analysis. Interview data were analysed using both inductive and deductive thematic analysis. Results. Data papers share several discourse components with traditional academic papers but also include unique components such as Data Value (V), Usage Notes (U), Data Availability (A), and Quality Control (Q). A total of 18 types of data events were identified. Data reusers' needs were categorized into five dimensions: data collection, content, structure, analysis, and reuse. Reusers perceive the functional, social, and cognitive value of data papers through research actions. Conclusion(s). Data papers meet foundational needs in discovery, filtering, and comprehension, but fail to address application-level needs like trust assessment, accessibility, and reconstruction hints. This study also indicates the importance of data papers’ linking with data repositories and corresponding academic papers.
Copyright (c) 2026 Cuiyu Qin, Qingyu Duan, Lei Xu, Xiaoguang Wang https://creativecommons.org/licenses/by-nc/4.0
AI for research assessment: opportunities and challenges from India
Introduction. Artificial intelligence (AI) is beginning to reshape the infrastructures of scholarly communication, raising important questions about trust and transparency. This study examines researchers’ perspectives on AI-driven scientific replication prediction tools as emerging components of research assessment. Method. Qualitative, in-depth, semi-structured interviews were conducted with 19 faculty and doctoral scholars in India to explore how researchers perceive and engage with the scientific replication AI tool. Analysis. Our analysis focused on how information practices, institutional incentives, and sociocultural contexts shape the adoption of AI technologies in scholarly work. Interview transcripts were studied using thematic analysis using a collaborative and iterative coding process. Results. Participants mention that limited funding, infrastructure, and access to advanced tools or high-quality datasets make replicating studies difficult in India. They recognised the value of AI tools for surfacing reproducibility assessments during literature reviews and study design. They advocated for hybrid human–AI systems that balance the efficiency of automation with the nuanced judgment of experts. Conclusion. This study situates AI replication tools within broader scholarly infrastructures, highlighting the need for design features that enhance explainability, fairness, and cultural sensitivity. It also represents the challenges faced by Indian researchers when it comes to replication and open science
Copyright (c) 2026 Tatiana Chakravorti, Chuhao Wu, Sai Koneru, Sarah Rajtmajer https://creativecommons.org/licenses/by-nc/4.0
An empirical analysis of open access citation advantages in library and information science
Introduction. This study examines the citation impact of open access (OA) articles in library and information science (LIS). Given limited OA research in LIS compared to other fields, it contributes by examining OA citation advantages over time, journal quartile, OA type, and discipline. Method. Using a dataset of 109,759 LIS journal articles (2001–2024) from WoS, the study classified articles by OA status and type, then applied statistical analyses, including t-tests, ANOVA and time-series analysis. Analysis. Both parametric and nonparametric tests compared citation impacts across OA types, disciplinary scope, publication years, and journal quartiles. Effect sizes were calculated to assess practical relevance. Results. Non-OA articles received slightly more citations (mean 18.83) than OA articles (mean 17.9), though the difference was minimal. Green OA showed the largest citation advantage (28.55 average). OA citation advantages declined from 9.75 citations (2001–2004) to 0.74 (2020–2024). Multi-disciplinary articles fared better than single-discipline articles. Conclusion(s). The study reveals that OA citation advantages in LIS are conditional, varying by OA type, discipline, and period. These findings caution against generalizing the OA citation benefits observed in other fields.
Copyright (c) 2026 Sunwoo Lee, Wonsik Shim https://creativecommons.org/licenses/by-nc/4.0
Bibliographic records reveal trends in Chinese history scholarship: Evidence from Library of Congress metadata
Introduction. Books are key research outputs in the humanities, but often poorly indexed in scholarly databases. This paper presents a preliminary analysis of metadata in the Library of Congress (LC) to analyse scholarship on Chinese history. Method. We extracted metadata of all 18,564 books on Chinese history from LC published in three major regions, Greater China, the U.S., and Europe, and mapped chronological information of each book onto historical periods. Analysis. We conducted quantitative analysis on the information to understand the general publication trends of books on Chinese history and their historical period representation, both the overall patterns and the similarities and differences within the three regions. Results. Two major surges appear in Greater China and U.S. publications, with Greater China leading since the 1980s and the U.S. surpassing Europe by the 1960s. Later periods attract more exclusive attention, while earlier periods are often embedded in multi-dynastic narratives in Western scholarship, though U.S. research has recently diversified. Conclusion. This study pioneers the use of bibliographic records to analyse Chinese historiography, offering a complement to scholarship focused on canonical works and highlighting the value of library metadata for quantitative humanities research. We share our dataset and code at https://anonymous.4open.science/r/Code-for-Analysis-of-Chinese-History-Collection-in-the-Library-of-Congress-Catalog6BC2.
Copyright (c) 2026 Kai Li , Wenyi Shang, Yingying Han https://creativecommons.org/licenses/by-nc/4.0
Ensuring the long-term accessibility of scholarly blogs: Bloggers’ attitudes and practices
Introduction. This study explores the integration of scholarly blogs into digital research and information infrastructures, focusing on the attitudes and practices of German scholarly bloggers regarding the long-term accessibility of their blogs. Method and Analysis. We conducted 13 semi-structured interviews with scholarly bloggers. The interview transcripts were coded in MAXQDA 24 using a qualitative thematic approach. Results. Findings reveal that participants recognise the importance of making their blogs long-term accessible and express a desire for their integration into existing digital infrastructures. However, they also face organisational challenges and varying levels of engagement in preservation practices, ranging from obtaining formal identifiers like ISSNs and DOIs to relying on individual strategies such as local backups. Conclusions. This study emphasizes the need for clearer guidelines and support systems to facilitate the long-term accessibility of scholarly blogs. While bloggers generally recognise the importance of long-term accessibility, digital research and information infrastructures do not yet sufficiently offer solutions for bloggers.
Copyright (c) 2026 Catharina Ochsner, Heinz Pampel https://creativecommons.org/licenses/by-nc/4.0
‘Ugh, it’s a difficult topic’: Positionality statements as information use in information and library science research
Introduction. The effects of information use remain understudied. We fill a key gap in the literature by conducting an empirical study of positionality statement use in information and library science (ILS) research. We analyse why information and library scientists endorse or object to these statements. Method. Using Qualtrics software, we conducted an international online survey of information and library scientists. Our instrument included demographic data, closed-ended questions, Likert-type items, and open-ended questions. Analysis. We conducted both quantitative and qualitative analyses on the data, which related to 213 respondents. Our quantitative analysis employed the statistical package SPSS, while qualitative analysis employed NVivo software. Results. Quantitative findings showed significant correlations between variables. Qualitative findings demonstrated that participants valued positionality but felt profound ambivalence concerning positionality statement use. They registered 10 strengths and 12 weaknesses of this information use. Conclusion(s). We offer both recommendations for practice and questions for further research. Further emphasis on raising awareness of positionality and developing both educational tools and best practices for using positionality statements is urgent. Also needed is more scholarly exploration of the effects of information use.
Copyright (c) 2026 Alex H. Poole, Ashley Todd-Diaz https://creativecommons.org/licenses/by-nc/4.0