The Network Life of Non-biomedical Knowledge: Mapping Vietnamese Traditional Medicine Discourses on Facebook

Authors

  • Dang Nguyen School of Historical and Philosophical Studies, University of Melbourne, Australia

DOI:

https://doi.org/10.33621/jdsr.v3i2.82

Keywords:

non-biomedical knowledge, traditional medicine, social network analysis, topic modeling, LDA, Vietnam

Abstract

Traditional medicine is hugely popular throughout Southeast Asia and other parts of the world. The development of the internet and online social networks in these contexts has enabled a significant proliferation of non-biomedical knowledge and practices via platforms such as Facebook. People use Facebook to advocate for non- biomedical alternatives to unaffordable biomedicine, share family medical recipes, discuss medicinal properties of indigenous plants, buy and sell these plants, and even crowdsource disease diagnoses. This paper examines the network characteristics of, and discourses present within, three popular Vietnamese non-biomedical knowledge Facebook sites over a period of five years. These large-scale datasets are studied using social network analysis and generative statistical models for topic analysis (Latent Dirichlet allocation). Forty-nine unique topics were quantitatively identified and qualitatively interpreted. Among these topics, themes of religion and philanthropy, critical discussions of traditional medicine, and negotiations involving overseas Vietnamese were particularly notable. Although non-biomedical networks on Facebook are growing both in terms of scale and popularity, sub-network comment activities within these networks exhibit ‘small world’ characteristics. This suggests that social media seem to be replicating existing social dynamics that historically enable the maintenance of traditional forms of medical knowledge, rather than transforming them here.

References

Albright, J. (2018). The Graph API: Key Points in the Facebook and Cambridge Analytica Debacle. Medium. Available at https://medium.com/tow-center/the-graph-api-key-points-in-the-facebook-and-cambridge-analytica-debacle-b69fe692d747

Arun, R., Suresh, V., Madhavan, C. V., & Murthy, M. N. (2010). On finding the natural number of topics with latent dirichlet allocation: Some observations. In Pacific-Asia conference on knowledge discovery and data mining (pp. 391-402). Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-13657-3_43

Blei, D. M. (2012). Surveying a suite of algorithms that offer a solution to managing large document archives. Communication of the ACM, 55(4), 77-84. DOI: 10.1145/2133806.2133826

Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of machine Learning research, 3, 993-1022.

Blei, D.M., Mcauliffe, J. (2007). Supervised topic models. Neural Information Processing Systems Proceedings. 121-128. DOI: 10.5555/2981562.2981578

Caci, B., Cardaci, M., & Tabacchi, M. E. (2012). Facebook as a small world: a topological hypothesis. Social Network Analysis and Mining, 2(2), 163-167. DOI: 10.1007/s13278-011-0042-8

Cao, J., Xia, T., Li, J., Zhang, Y., & Tang, S. (2009). A density-based method for adaptive LDA model selection. Neurocomputing, 72(7-9), 1775-1781. DOI: 10.1016/j.neucom.2008.06.011

Castells, M. (1996). The rise of the network society. Malden, Mass, Blackwell Publishers. DOI: 10.1002/9781444319514

Castells, M. (1997). Power of identity: The information age: Economy, society, and culture. Blackwell Publishers. DOI: 1002/9781444318234

Castells, M. (1998). End of Millennium: The Information Age: Economy, Society and Culture. Oxford and Maiden: Blackwell Publishers.

Catanese, S. A., De Meo, P., Ferrara, E., Fiumara, G., & Provetti, A. (2011, May). Crawling facebook for social network analysis purposes. In Proceedings of the international conference on web intelligence, mining and semantics. pp. 1-8. DOI: 10.1145/1988688.1988749

Craig, D. (2002). Familiar medicine: Everyday health knowledge and practice in today's Vietnam. University of Hawaii Press. USA. DOI: 10.1017/S0021911804001500

Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695(5), 1-9.

DiMaggio, P. (2015). Adapting computational text analysis to social science (and vice versa). Big Data & Society, 2(2), 1-5. DOI: 10.1177/2053951715602908

Epskamp, S., Costantini, G., Haslbeck, J., Cramer, A. O., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2019). Package ‘qgraph’. Available at https://cran.r-project.org/web/packages/qgraph/qgraph.pdf.

Feather, J., 2013. The information society: A study of continuity and change. 6th edition. Facet publishing. London, UK. DOI: 10.1108/00220410510632121

Gerlach, M., Peixoto, T. P., & Altmann, E. G. (2018). A network approach to topic models. Science advances, 4(7), eaaq1360. DOI: 10.1126/sciadv.aaq1360

Graham, T. & Ackland, R. (2016). SocialMediaLab: Tools for collecting social media data and generating networks for analysis. CRAN (The Comprehensive R Archive Network). Retrieved from https://cran.rproject.org/web/packages/SocialMediaLab/SocialMediaLab.pdf

Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National academy of Sciences, 101(suppl 1), 5228-5235. DOI: 10.1073/pnas.0307752101

Grün, B. & Hornik, K. (2011). topicmodels: An R package for fitting topic models. Journal of Statistical Software, 40(13), 1-30. DOI: 10.18637/jss.v040.i13

Hether, H. J., Murphy, S. T., & Valente, T. W. (2016). A social network analysis of supportive interactions on prenatal sites. Digital health, 2, pp. 1-12. DOI: 10.1177/2055207616628700

Hoang, T. A. (2015). Modeling user interest and community interest in microbloggings: An integrated approach. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 708-721). Springer, Cham. DOI: 10.1007/978-3-319-18038-0_55

Hou-Liu, J. (2018). Benchmarking and Improving Recovery of Number of Topics in Latent Dirichlet Allocation Models. Available at https://pdfs.semanticscholar.org/2175/aa77463e23da96281cc2fb5125e0b9de3bbd.pdf

Humphries, M. D., & Gurney, K. (2008). Network ‘small-world-ness’: a quantitative method for determining canonical network equivalence. PLoS One, 3(4), e0002051. DOI: 10.1371/journal.pone.0002051

Kemp, S., 2019a, Digital 2019: Global Digital Overview, DataReportal, viewed 12 December 019 < https://datareportal.com/reports/digital-2019-global-digital-overview>

Kemp, S., 2019b, Digital 2019: Vietnam, DataReportal, viewed 12 December 2019 < <https://datareportal.com/reports/digital-2019-vietnam>

Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory: Oxford University Press. UK.

Law, J., & Mol, A. (1995). Notes on materiality and sociality. The sociological review, 43(2), 274-294. DOI: 10.1111/j.1467-954X.1995.tb00604.x

Liebeskind, C., & Liebeskind, S. (2018). Identifying Abusive Comments in Hebrew Facebook. In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE) (pp. 1-5). IEEE. DOI: 10.1109/ICSEE.2018.8646190

Lu, X., Yu, Z., Guo, B., & Zhou, X. (2014). Predicting the content dissemination trends by repost behavior modeling in mobile social networks. Journal of Network and Computer Applications, 42, 197-207. DOI: 10.1016/j.jnca.2014.01.015

Ma, S., Zhang, C., & He, D. (2016). Document representation methods for clustering bilingual documents. In Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology (p. 65). American Society for Information Science. DOI: 10.1002/pra2.2016.14505301065

Maier, D., Waldherr, A., Miltner, P., Wiedemann, G., Niekler, A., Keinert, A., Pfetscha, B., Heyerc, G., Reberd, U., Ha?usslerd, T., Schmid-Petrie, H. & Adam, S. (2018). Applying LDA topic modeling in communication research: Toward a valid and reliable methodology. Communication Methods and Measures, 12(2-3), 93-118. DOI: 10.1080/19312458.2018.1430754

Minh Huy (2018). ‘Overseas remittances to Vietnam continue increasing’. Sai Gon Giai Phong News Online. Available at https://m.sggpnews.org.vn/business/overseas-remittances-to-vietnam-continue-increasing-79438.html.

Mol, A. (2008). The logic of care: Health and the problem of patient choice. Routledge. UK. DOI: 10.1111/j.1467-9566.2009.1168_2.x

Mol, A.P., 2009. Environmental governance through information: China and Vietnam. Singapore Journal of Tropical Geography, 30(1), pp.114-129. DOI: 10.1111/j.1467-9493.2008.00358.x

Monnais, L., Thompson, C. M., & Wahlberg, A. (Eds.). (2011). Southern medicine for southern people: Vietnamese medicine in the making. Cambridge Scholars Publishing. UK.

Nguyen, D. (2019). Mapping knowledge domains of non-biomedical modalities: A large-scale co-word analysis of literature 1987–2017. Social Science & Medicine, 233, 1-12. DOI: 10.1016/j.socscimed.2019.05.044

Nikita, M. (2016). Package ‘ldatuning’: Tuning of the Latent Dirichlet Allocation Models Parameters’. r package version 1.0.0. Available at https://CRAN.R project.org/package=ldatuning

Ortmann S. (2017) The Vietnamese Government and Institutional Reforms. In: Environmental Governance in Vietnam. Palgrave Macmillan, Cham. DOI: 10.1007/978-3-319-49760-0_3

Paul, M. J., & Dredze, M. (2012). A model for mining public health topics from Twitter. Health, 11(16-16), 1.

Ríssola, E. A., Bahrainian, S. A., & Crestani, F. (2019). Anticipating Depression Based on Online Social Media Behaviour. In International Conference on Flexible Query Answering Systems (pp. 278-290). Springer, Cham. DOI: 10.1007/978-3-030-27629-4_26

Singer, M., Baer, H., Long, D., & Pavlotski, A. (2019). Introducing medical anthropology: a discipline in action. Rowman & Littlefield. USA.

Smith, N., & Graham, T. (2019). Mapping the anti-vaccination movement on Facebook. Information, Communication & Society, 22(9), 1310-1327. DOI: 10.1080/1369118X.2017.1418406

Statt, N. 2019. ‘Facebook is redesigning its core app around the two parts people actually like to use’. The Verge. Available at https://www.theverge.com/2019/4/30/18523265/facebook-events-groups-redesign-news-feed-features-f8-2019.

Thompson, C. M. (2017). The implications of gia truy?n: Family transmission texts, medical authors, and social class within the healing community in Vietnam. South East Asia Research, 25(1), 34-46. DOI: 10.1177/0967828X17690045

Uzzi, B., & Spiro, J. (2005). Collaboration and creativity: The small world problem. American journal of sociology, 111(2), 447-504. DOI: 10.1086/432782

Van Dijck, J., & Poell, T. (2013). Understanding social media logic. Media and communication, 1(1), 2-14. DOI: 10.17645/mac.v1i1.70

Vu, T., Nguyen, D. Q., Nguyen, D. Q., Dras, M., & Johnson, M. (2018). VnCoreNLP: A Vietnamese Natural Language Processing Toolkit. arXiv preprint arXiv:1801.01331. DOI: 10.18653/v1/N18-5012

Wang, W., Chen, R. R., Ou, C. X., & Ren, S. J. (2019). Media or message, which is the king in social commerce?: An empirical study of participants' intention to repost marketing messages on social media. Computers in Human Behavior, 93, 176-191. DOI: 10.1016/j.chb.2018.12.007

Watts, D. J. (1999). Networks, dynamics, and the small-world phenomenon. American Journal of Sociology, 105(2), 493-527. DOI: 10.1086/210318

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small world’ networks. Nature, 393(6684), 440-442. DOI: 10.1038/30918

Wittel, A. (2001). Toward a network sociality. Theory, culture & society, 18(6), 51-76. DOI: 10.1177/026327601018006003

Wohlgemuth, J., & Matache, M. T. (2012). Small world properties of Facebook group networks. University of Nebraska at Omaha. ProQuest Dissertations Publishing. DOI: 10.25088/ComplexSystems.23.3.197

Zhao, Y. (2018). An Investigation of Autism Support Groups on Facebook. Doctoral disseration. The University of Wisconsin-Milwaukee. Available at https://dc.uwm.edu/cgi/viewcontent.cgi?article=2968&context=etd.

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs Hachette Book Group. NY, US.

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Published

2021-06-28

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Research Articles

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