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http://dx.doi.org/10.15206/ajpor.2020.8.3.246

Predicting Health Communication Patterns in Follower-Influencer Networks: The Case of Taiwan Amid COVID-19  

Chang, Angela (University of Macau)
Jiao, Wen (University of Macau)
Publication Information
Asian Journal for Public Opinion Research / v.8, no.3, 2020 , pp. 246-264 More about this Journal
Abstract
As netizens increasingly utilize social media to obtain and engage with information, this study aims to determine the extent to which the follower-influencer interaction is manifested and strengthened. To analyze information related to the novel coronavirus disease (COVID-19), a total of 62,119 online posts from 11 Internet forums were examined to find a relationship between followers and influencers in Taiwan. These forums are PTT, SOGO, Ck101, Plurk, Mobile01, TalkFetnet, Gamez, PlaySport, Dcard, Eyny, and PCDVD. The variables that were the best predictors of influencer classification were strong influences, engagements, and hot values across 11 Internet forums. Learning the response to the COVID-19 pandemic is vital because public actions could have been fueled by stigmatizing terms that may harm public health and well-being. The results questioned the conventional diffusion of traditional news sources because the influencers brought widespread attention to the health threat issues in the early outbreak stages. This study enhances the understanding of forum types, follower engagement, and influencers' impact maximization in social networks. The conclusion provides insight into the relationships and information diffusion mechanisms to ensure accurate health information dissemination.
Keywords
followership; risk communication; Internet forum; engagement; health information; COVID-19;
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1 Blakemore, J. K., Bayer, A. H., Smith, M. B., & Grifo, J. A. (2020). Infertility influencers: An analysis of information and influence in the fertility webspace. Journal of Assisted Reproduction and Genetics, 37, 1371-1378. https://doi.org/10.1007/s10815-020-01799-2   DOI
2 Burt, R. S. (1999). The social capital of opinion leaders. The ANNUALS of the American Academy of Political and Social Science, 566(1), 37-54. https://doi.org/10.1177/000271629956600104   DOI
3 Butler, B. S. (2001). Membership size, communication activity, and sustainability: A resource-based model of online social structures. Information Systems Research, 12(4), 346-362. https://doi.org/10.1287/isre.12.4.346.9703   DOI
4 Cao, L., & Tang, X. (2014). Topics and trends of the on-line public concerns based on Tianya forum. Journal of Systems Science and Systems Engineering, 23(2), 212-230. https://doi.org/10.1007/s11518-014-5243-z   DOI
5 Case, D. O., Johnson, J. D., Andrews, J. E., Allard, S. L., & Kelly, K. M. (2004). From twostep flow to the Internet: The changing array of sources for genetics information seeking. Journal of the American Society for Information Science and Technology, 55(8), 660-669. https://doi.org/10.1002/asi.20000   DOI
6 Chang, A., Hu, J., Liu, Y., & Liu, M. T. (2019). Data mining approach to Chinese food analysis for diet-related cardiometabolic diseases. Proceedings of 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW), 91-95. https://doi.org/10.1109/ICDEW.2019.00-29
7 Choi, S. (2015). The two-step flow of communication in Twitter-based public forums. Social Science Computer Review, 33(6), 696-711. https://doi.org/10.1177/0894439314556599   DOI
8 Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola, P., Zollo, F., & Scala, A. (2020). The COVID-19 social media infodemic. https://arxiv.org/abs/2003.05004
9 Cui, X., Yang, N., Wang, Z., Hu, C., Zhu, W., Li, H., Ji, Y., & Liu, C. (2015). Chinese social media analysis for disease surveillance. Personal and Ubiquitous Computing, 19(7), 1125-1132. https://doi.org/10.1007/s00779-015-0877-5   DOI
10 Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A., & Larson, H. (2020). The pandemic of social media panic travels faster than the COVID-19 outbreak. Journal of Travel Medicine, 27(3), 1-2. https://doi.org/10.1093/jtm/taaa031
11 Kumar, A., & Garg, G. (2019). Systematic literature review on context-based sentiment analysis in social multimedia. Multimedia Tools and Applications, 79, 15349-15380. https://doi.org/10.1007/s11042-019-7346-5   DOI
12 Huffaker, D. (2010). Dimensions of leadership and social influence in online communities. Human Communication Research, 36(4), 593-617. https://doi.org/10.1111/j.1468-2958.2010.01390.x   DOI
13 Johns Hopkins Coronavirus Resource Center. (2020). COVID-19 dashboard by the center for systems science and engineering at Johns Hopkins University. Johns Hopkins University. Retrieved June 20, 2020 from https://coronavirus.jhu.edu/map.html
14 Kim, S., & Yoon, J. (2011). The use of an online forum for health information by married Korean women in the U.S. Information Research, 17(2). 1-18. https://scholarcommons.usf.edu/si_facpub/129/
15 Li, L. X. (2014). Involvement of social media in disaster management during the Wenchuan and Ya’an Earthquakes. Asian Journal for Public Opinion Research, 1(4), 249-267. https://doi.org/10.15206/ajpor.2014.1.4.249   DOI
16 Li, W.-J., Dong, Q., Shi, Y.-B., Fu, Y., & He, J.-L. (2017). Effect of recent popularity on heat-conduction based recommendation models. Physica A: Statistical Mechanics and Its Applications, 474, 334-343. https://doi.org/10.1016/j.physa.2017.01.042   DOI
17 Liang, T. P., & Lai, H. J. (2002). Discovering user interests from web browsing behavior: An application to Internet news services. Proceedings of the 35th Annual Hawaii International Conference on System Sciences. 2718-2727. https://doi.org/10.1109/HICSS.2002.994214
18 Liu, J. G., Zhou, T., & Guo, Q. (2011). Information filtering via biased heat conduction. Physical Review E, 84(3), 037101. https://doi.org/10.1103/PhysRevE.84.037101   DOI
19 Lou, C., Tan, S.-S., & Chen, X. (2019). Investigating consumer engagement with influencer- vs. brand-promoted ads: The roles of source and disclosure. Journal of Interactive Advertising, 19(3), 169-186. https://doi.org/10.1080/15252019.2019.1667928   DOI
20 Lou, C., & Alhabash, S. (2020). Alcohol brands being socially responsible on social media? When and how warning conspicuity and warning integration decrease the efficacy of alcohol brand posts among under-drinking-age youth. Journal of Interactive Advertising, 1-46. https://doi.org/10.1080/15252019.2020.1780651
21 Ma, W., Feng, X., Wang, S., & Gong, M. (2016). Personalized recommendation based on heat bidirectional transfer. Physica A: Statistical Mechanics and Its Applications, 444, 713-721. https://doi.org/10.1016/j.physa.2015.10.068   DOI
22 Schafer, M. S., & Taddicken, M. (2015). Opinion leadership mediatized opinion leaders: New patterns of opinion leadership in new media environments? International Journal of Communication, 9, 960-981. https://ijoc.org/index.php/ijoc/article/view/2778
23 Meijer, I. C., & Kormelink, T. G. (2015). Checking, sharing, clicking and linking: Changing patterns of news use between 2004 and 2014. Digital Journalism, 3(5), 664-679. https://doi.org/10.1080/21670811.2014.937149   DOI
24 Peacock, C., & Leavitt, P. (2016). Engaging young people: Deliberative preferences in discussions about news and politics. Social Media + Society, 2(1), 1-11. https://doi.org/10.1177/2056305116637096
25 Preece, J., & Maloney-Krichmar, D. (2003). Online communities. In J. Jacko & A. Sears (Eds.), Handbook of human-computer interaction (pp. 596-620). Lawrence Erlbaum Associates Inc.
26 SimilarWeb Website Ranking. (2020, June 1). Top sites ranking for all categories in Taiwan. SimilarWeb. Retrieved June 1, 2020 from https://www.similarweb.com/zh/top-websites/taiwan/
27 Song, S., & Meng, Y. (2015). Classifying and ranking microblogging hashtags with news categories. Proceedings of 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS), 540-541. https://doi.org/10.1109/RCIS.2015.7128928
28 Tanner, E. (2001). Chilean conversations: Internet forum participants debate Augusto Pinochet's detention. Journal of Communication, 51(2), 383-403. https://doi.org/10.1111/j.1460-2466.2001.tb02886.x   DOI
29 Taiwan Centers for Disease Control. (2020, June 27). COVID-19 (SARS-CoV-2 infection). Ministry of Health and Welfare. Retrieved June 27, 2020 from https://www.cdc.gov.tw/En
30 Taiwan Network Information Center. (2019, n.d.). Taiwan Internet report 2019. https://report.twnic.tw/2019/index_en.html
31 Yoo, Y., & Alavi, M. (2004). Emergent leadership in virtual teams: What do emergent leaders do? Information and Organization, 14(1), 27-58. https://doi.org/10.1016/j.infoandorg.2003.11.001   DOI
32 Wang, P. W., Su, Y. J., Shih, M. L., & Luo, S. D. (2010). Analysis of online word-of-mouth in online forums regarding notebook computers. Journal of Convergence Information Technology, 5(5), 118-124. https://doi.org/10.4156/jcit.vol5.issue5.13   DOI
33 Weeks, B. E., Ardevol-Abreu, A., & Gil de Zuniga, H. (2017). Online influence? Social media use, opinion leadership, and political persuasion. International Journal of Public Opinion Research, 29(2), 214-239. https://doi.org/10.1093/ijpor/edv050
34 Welbers, K., & Opgenhaffen, M. (2019). Presenting news on social media: Media logic in the communication style of newspapers on Facebook. Digital Journalism, 7(1), 45-62. https://doi.org/10.1080/21670811.2018.1493939   DOI
35 Zhang, L., Zhao, J., & Xu, K. (2016). Who creates trends in online social media: The crowd or opinion leaders? Journal of Computer-Mediated Communication, 21(1), 1-16. https://doi.org/10.1111/jcc4.12145   DOI
36 Zhao, J., Lui, J. C., Towsley, D., & Guan, X. (2014). Whom to follow: Efficient followee selection for cascading outbreak detection on online social networks. Computer Networks, 75, 544-559. https://doi.org/10.1016/j.comnet.2014.08.024   DOI
37 Zhou, Y., & Moy, P. (2007). Parsing framing processes: The interplay between online public opinion and media coverage. Journal of Communication, 57(1), 79-98. https://doi.org/10.1111/j.0021-9916.2007.00330.x
38 Zubiaga, A. (2019). Mining social media for newsgathering: A review. Online Social Networks and Media, 13, 1-9. https://doi.org/10.1016/j.osnem.2019.100049   DOI