Analyzing radical visuals at scale

How far-right groups mobilize on TikTok

Authors

  • Julian Hohner Ludwig Maximilian University of Munich, Germany
  • Azade Esther Kakavand University of Vienna, Austria
  • Sophia Rothut Ludwig Maximilian University of Munich, Germany

DOI:

https://doi.org/10.33621/jdsr.v6i1.200

Keywords:

TikTok, Mobilization, Image Classification, Mixed Methods, Far Right, Radicalization, Protest

Abstract

Research examining radical visual communication and its manifestation on the trending platform TikTok is limited. This paper presents a novel methodological framework for studying mobilization strategies of far-right groups on TikTok, employing a mixed-method approach that combines manual annotation, unsupervised image classification, and named-entity recognition to analyze the dynamics of radical visuals at scale. Differentiating between internal and external mobilization, we use popularity and engagement cues to investigate far-right mobilization efforts on TikTok within and outside their community. Our findings shed light on the effectiveness of unsupervised image classification when utilized within a broader mixed-method framework, as each observed far-right group employs unique platform characteristics. While Conspiracists flourish in terms of overall popularity and internal mobilization, nationalist and protest content succeeds by using a variety of persuasive visual content to attract and engage external audiences. The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media.

References

Albertazzi, D., & Bonansinga, D. (2023). Beyond anger: The populist radical right on TikTok. Journal of Contemporary European Studies, 1–17. https://doi.org/10.1080/14782804.2022.2163380

Arief, R., Mutiara, A., Kusuma, T., & Hustinawaty. (2018). Automated extraction of large scale scanned document images using Google Vision OCR in Apache Hadoop environment. International Journal of Advanced Computer Science and Applications, 9, 112–116. https://doi.org/10.14569/IJACSA.2018.091117

Ayanian, A. H., Böckler, N., Doosje, B., & Zick, A. (2019). Processes of Radicalization and Polarization in the Context of Transnational Islamist Terrorism. International Journal of Conflict and Violence, 1–6. https://doi.org/10.4119/IJCV-3098

Baker, S. A. (2022). Alt. Health Influencers: How wellness culture and web culture have been weaponised to promote conspiracy theories and far-right extremism during the COVID-19 pandemic. European Journal of Cultural Studies, 25 (1), 3–24. https://doi.org/10.1177/13675494211062623

Bennett, W. L., & Segerberg, A. (2012). THE LOGIC OF CONNECTIVE ACTION: Digital media and the personalization of contentious politics. Information, Communication & Society, 15 (5), 739–768. https://doi.org/10.1080/1369118X.2012.670661

Boucher, V. (2022). Down the TikTok Rabbit Hole: Testing the TikTok Algorithm’s Contribution to Right Wing Extremist Radicalization (thesis). Retrieved May 2, 2023, from https://qspace.library.queensu.ca/handle/1974/30197

Boulianne, S., & Lee, S. (2022). Conspiracy Beliefs, Misinformation, Social Media Platforms, and Protest Participation. Media and Communication, 10 (4), 30–41. https://doi.org/10.17645/mac.v10i4.5667

Brown, K., Mondon, A., & Winter, A. (2023). The far right, the mainstream and mainstreaming: Towards a heuristic framework. Journal of Political Ideologies, 28(2), 162-179. https://doi.org/10.1080/13569317.2021.1949829

Caiani, M. (2022). Between real and virtual: Strategies of mobilisation of the radical right in Eastern Europe. East European Politics, 38 (3), 331–357. https://doi.org/10.1080/21599165.2021.1955676

Caiani, M., Porta, D. d., & Wagemann, C. (2012). Mobilizing on the Extreme Right: Germany, Italy, and the United States. Oxford University Press.

Carter, E. (2018). Right-wing extremism/radicalism: Reconstructing the concept. Journal of Political Ideologies, 23 (2), 157–182. https://doi.org/10.1080/13569317.2018.1451227

Castelli Gattinara, P., Froio, C., & Pirro, A. L. P. (2022). Far-right protest mobilisation in Europe: Grievances, opportunities and resources. European Journal of Political Research, 61 (4), 1019–1041. https://doi.org/10.1111/1475-6765.12484

Cervi, L., & Divon, T. (2023). Playful Activism: Memetic Performances of Palestinian Resistance in TikTok #Challenges. Social Media + Society, 9 (1), 1–13. https://doi.org/10.1177/20563051231157607

Cervi, L., Tejedor, S., & Marín Lladó, C. (2021). TikTok and the new language of political communication. Cultura, Lenguaje y Representación, 26, 267–287. https://doi.org/10.1177/20563051231157607

Chapelan, A. (2021). “Swallowing the red pill”: The coronavirus pandemic and the political imaginary of stigmatized knowledge in the discourse of the far-right. Journal of Transatlantic Studies, 19 (3), 282–312. https://doi.org/10.1057/s42738-021-00073-2

Chen, S.-H., & Chen, Y.-H. (2017). A Content-Based Image Retrieval Method Based on the Google Cloud Vision API and WordNet. In N. T. Nguyen, S. Tojo, L. M. Nguyen, & B. Trawi?ski (Eds.), Intelligent Information and Database Systems (pp. 651–662). Springer International Publishing. https://doi.org/10.1007/978-3-319-54472-4_61

Clever, L., Schatto-Eckrodt, T., Clever, N. C., & Frischlich, L. (2023). Behind Blue Skies: A Multimodal Automated Content Analysis of Islamic Extremist Propaganda on Instagram. Social Media + Society, 9 (1), 1–14. https://doi.org/10.1177/20563051221150404

Collins, L. M., & Lanza, S. T. (2009). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. John Wiley & Sons.

Dinno, A. (2015). Nonparametric Pairwise Multiple Comparisons in Independent Groups using Dunn’s Test. The Stata Journal, 15 (1), 292–300. https://doi.org/10.1177/1536867X1501500117

Ekman, M. (2022). The great replacement: Strategic mainstreaming of far-right conspiracy claims. Convergence: The International Journal of Research into New Media Technologies, 28 (4), 1127–1143. https://doi.org/10.1177/13548565221091983

Fuchs, M. (2023). Deutsche Politik auf Tik Tok. Retrieved May 1, 2023, from https://docs.google.com/spreadsheets/d/13yIKz_RdUe1IAExjJKiPlgzkD- T0ZXRbEnU2nIkDJFU/edit#gid=0

Gao, Y., Liu, F., & Gao, L. (2023). Echo chamber effects on short video platforms. Scientific Reports, 13 (6282), 1–17. https://doi.org/10.1038/s41598-023-33370-1

Goodwin, A., Joseff, K., Riedl, M. J., Lukito, J., & Woolley, S. (2023). Political Relational Influencers: The Mobilization of Social Media Influencers in the Political Arena [Number: 0]. International Journal of Communication, 17, 1613–1633. Retrieved May 4, 2023, from https://ijoc.org/index.php/ijoc/article/view/18987

Grandinetti, J., & Bruinsma, J. (2022). The Affective Algorithms of Conspiracy TikTok. Journal of Broadcasting & Electronic Media, 1–20. https://doi.org/10.1080/08838151.2022.2140806

Heiss, R., Schmuck, D., & Matthes, J. (2019). What drives interaction in political actors’ Facebook posts? Profile and content predictors of user engagement and political actors’ reactions. Information, Communication & Society, 22 (10), 1497–1513. https://doi.org/10.1080/1369118X.2018.1445273

Hosseini, H., Xiao, B., & Poovendran, R. (2017). Google’s Cloud Vision API is Not Robust to Noise. 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), 101–105. https://doi.org/10.1109/ICMLA.2017.0-172

Hunger, S., Hutter, S., & Kanol, E. (2023). The mobilisation potential of anti-containment protests in Germany. West European Politics, 46 (4), 812–840. https://doi.org/10.1080/01402382.2023.2166728

Hutter, S., Kanol, E., Gonzatti, D. S., Schürmann, L., Völker, T., & Koopmans, R. (2023). Protest and Radicalization. In U. Kemmesies, P. Wetzels, B. Austin, C. Büscher, A. Dessecker, & S. Hutter (Eds.), MOTRA-Monitor 2022 (pp. 110-135). https://doi.org/10.53168/ISBN.978-3-9818469-6-6_2023_MOTRA

Karnowski, V. (2017). Latent Class Analysis. In J. Matthes, C. S. Davis, & R. F. Potter (Eds.), The International Encyclopedia of Communication Research Methods (1st ed., pp. 1–10). Wiley. https://doi.org/10.1002/9781118901731.iecrm0130

Lin, Y., Lv, F., Zhu, S., Yang, M., Cour, T., Yu, K., Cao, L., & Huang, T. (2011). Large-scale image classification: Fast feature extraction and SVM training. CVPR 2011, 1689–1696. https://doi.org/10.1109/CVPR.2011.5995477

Little, O., & Richards, A. (2021). TikTok’s algorithm leads users from transphobic videos to far-right rabbit holes. Retrieved May 3, 2023, from https://www.mediamatters.org/tiktok/tiktoks-algorithm-leads-users-transphobic- videos-far-right-rabbit-holes

Macafee, T. (2013). Some of these things are not like the others: Examining motivations and political predispositions among political Facebook activity. Computers in Human Behavior, 29 (6), 2766–2775. https://doi.org/10.1016/j.chb.2013.07.019

Marengo, D., Settanni, M., & Montag, C. (2022). Dataset on individual differences in self-reported personality and inferred emotional expression in profile pictures of Italian Facebook users. Data in Brief, 41, 10–10. https://doi.org/10.1016/j.dib.2022.107899

Medina Serrano, J. C., Papakyriakopoulos, O., & Hegelich, S. (2020). Dancing to the Partisan Beat: A First Analysis of Political Communication on TikTok. 12th ACM Conference on Web Science, 257–266. https://doi.org/10.1145/3394231.3397916

Mitts, T., Phillips, G., & Walter, B. F. (2022). Studying the Impact of ISIS Propaganda Campaigns. The Journal of Politics, 84 (2), 1220–1225. https://doi.org/10.1086/716281

Mudde, C. (2000). The ideology of the extreme right. Manchester University Press.

Newman, N. (2022). How publishers are learning to create and distribute news on TikTok / Reuters Institute for the Study of Journalism (tech. rep.). Reuters Institute. https://reutersinstitute.politics.ox.ac.uk/how-publishers-are-learning-create-and- distribute-news-tiktok

O’Callaghan, D., Greene, D., Conway, M., Carthy, J., & Cunningham, P. (2015). Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems. Social Science Computer Review, 33 (4), 459–478. https://doi.org/10.1177/0894439314555329

O’Connor, C. (2021). Hatescape: An In-Depth Analysis of Extremism and Hate Speech on TikTok (tech. rep. No. 24). Institute for Stategic Dialogue.

Omena, J. J., Elena, P., Gobbo, B., & Jason, C. (2021). The Potentials of Google Vision API-based Networks to Study Natively Digital Images. Diseña, 19 (1), 1–25. https://doi.org/10.7764/disena.19.Article.1

OpenAI. (2023). GPT-4 Technical Report. https://doi.org/10.48550/arXiv.2303.08774

Ostertagová, E., Ostertag, O., & Ková?, J. (2014). Methodology and Application of the Kruskal-Wallis Test. Applied Mechanics and Materials, 611, 115–120. https://doi.org/10.4028/www.scientific.net/AMM.611.115

Peng, Y. (2021). What Makes Politicians’ Instagram Posts Popular? Analyzing Social Media Strategies of Candidates and Office Holders with Computer Vision. The International Journal of Press/Politics, 26 (1), 143–166. https://doi.org/10.1177/1940161220964769

Pirro, A. L. P. (2023). Far right: The significance of an umbrella concept. Nations and Nationalism, 29 (1), 101–112. https://doi.org/10.1111/nana.12860

Pirro, A. L. P., & Gattinara, P. C. (2018). Movement Parties of the Far Right: The Organization and Strategies of Nativist Collective Actors. Mobilization: An International Quarterly, 23 (3), 367–383. https://doi.org/10.17813/1086-671X-23-3-367

Pre:Bunk. (2023). Rechtsextremismus und TikTok: Wie geht die Mobilisierung? Retrieved April 28, 2023, from https://www.belltower.news/rechtsextremismus-und-tiktok-teil-2-mobilisierung-148805/teil-2-mobilisierung-148805/

Rauchfleisch, A., & Kaiser, J. (2021). Deplatforming the Far-right: An Analysis of YouTube and BitChute. SSRN Electronic Journal, 1–28. https://doi.org/10.2139/ssrn.3867818

Rogers, R. (2020). Deplatforming: Following extreme Internet celebrities to Telegram and alternative social media. European Journal of Communication, 35 (3), 213–229. https://doi.org/10.1177/0267323120922066

Rosenstone, S. J., & Hansen, J. M. (1996). Mobilization, participation, and democracy in America. Pearson Education. Retrieved October 9, 2023, from https://cir.nii.ac.jp/crid/1130000796057872128

Rothut, S., Schulze, H., Hohner, J., & Rieger, D. (2023). Ambassadors of ideology: A conceptualization and computational investigation of far-right influencers, their networking structures, and communication practices. New Media & Society, 146144482311644. https://doi.org/10.1177/14614448231164409

Röchert, D., Weitzel, M., & Ross, B. (2020). The homogeneity of right-wing populist and radical content in YouTube recommendations. In International Conference on Social Media and Society (pp. 245-254). https://doi.org/10.1145/3400806.3400835

Schmid, A. (2013). Radicalisation, De-Radicalisation, Counter-Radicalisation: A Conceptual Discussion and Literature Review. Terrorism and Counter-Terrorism Studies, 1–91. https://doi.org/10.19165/2013.1.02

Schmid, U. K., Kümpel, A. S., & Rieger, D. (2022). How social media users perceive different forms of online hate speech: A qualitative multi-method study. New Media & Society, 0 (0), 1–19. https://doi.org/10.1177/14614448221091185

Schulze, H., Hohner, J., Greipl, S., Girgnhuber, M., Desta, I., & Rieger, D. (2022). Far-right conspiracy groups on fringe platforms: A longitudinal analysis of radicalization dynamics on Telegram. Convergence: The International Journal of Research into New Media Technologies, 28 (4), 1103–1126. https://doi.org/10.1177/13548565221104977

Schwemmer, C., Knight, C., Bello-Pardo, E. D., Oklobdzija, S., Schoonvelde, M., & Lockhart, J. W. (2020). Diagnosing Gender Bias in Image Recognition Systems. Socius: Sociological Research for a Dynamic World, 6, 1–17. https://doi.org/10.1177/2378023120967171

Schwemmer, C., Unger, S., & Heiberger, R. (2023). Automated image analysis for studying online behaviour. Research Handbook on Digital Sociology. Edward Elgar Publishing.

Stickings, T. (2021). ’Friendly face of National Socialism’: Leaked texts damage German far-right candidate. Retrieved April 27, 2023, from https://www.thenationalnews.com/world/europe/2021/08/03/friendly-face-of- national-socialism-leaked-texts-damage-german-far-right-candidate/

Tanoli, I., Pais, S., Cordeiro, J., & Jamil, M. L. (2022). Detection of Radicalisation and Extremism Online: A Survey (preprint). In Review. https://doi.org/10.21203/rs.3.rs-1185415/v1

Wang, M.-H., Chang, W.-Y., Kuo, K.-H., & Tsai, K.-Y. (2022). Analyzing Image-based Political Propaganda in Referendum Campaigns: From Elements to Strategies. https://doi.org/10.48550/arXiv.2205.13154

Weimann, G., & Masri, N. (2020). Research Note: Spreading Hate on TikTok. Studies in Conflict & Terrorism, 1–14. https://doi.org/10.1080/1057610X.2020.1780027

Weimann, G., & Masri, N. (2021). TikTok’s Spiral of Antisemitism. Journalism and Media, 2 (4), 697–708. https://doi.org/10.3390/journalmedia2040041

Weller, B. E., Bowen, N. K., & Faubert, S. J. (2020). Latent Class Analysis: A Guide to Best Practice. Journal of Black Psychology, 46 (4), 287–311. https://doi.org/10.1177/0095798420930932

Williams, N. W., Casas, A., & Wilkerson, J. D. (2020). Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification. Elements in Quantitative and Computational Methods for the Social Sciences, 1–21. https://doi.org/10.1017/9781108860741

Xi, N., Ma, D., Liou, M., Steinert-Threlkeld, Z. C., Anastasopoulos, J., & Joo, J. (2020). Understanding the Political Ideology of Legislators from Social Media Images. Proceedings of the International AAAI Conference on Web and Social Media, 14, 726–737. https://doi.org/10.1609/icwsm.v14i1.7338

Zehring, M., & Domahidi, E. (2023). German Corona Protest Mobilizers on Telegram and Their Relations to the Far Right: A Network and Topic Analysis [Publisher: SAGE Publications Ltd]. Social Media + Society, 9 (1), 20563051231155106. https://doi.org/10.1177/20563051231155106

Zeng, J., & Kaye, D. B. V. (2022). From content moderation to visibility moderation : A case study of platform governance on TikTok. Policy & Internet, 14 (1), 79–95. https://doi.org/10.1002/poi3.287

Zulli, D., & Zulli, D. J. (2022). Extending the Internet meme: Conceptualizing technological mimesis and imitation publics on the TikTok platform. New Media & Society, 24 (8), 1872–1890. https://doi.org/10.1177/1461444820983603

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2024-03-06

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