Published on in Vol 7, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26090, first published .
Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study

Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study

Characterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study

Journals

  1. Lotto M, Santana Jorge O, Sá Menezes T, Ramalho A, Marchini Oliveira T, Bevilacqua F, Cruvinel T. Psychophysiological Reactions of Internet Users Exposed to Fluoride Information and Disinformation: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2022;11(6):e39133 View
  2. Yu H, Yu G, Li Y, Li T. Study on the communication effect of the social livestream of cabin hospitals' construction process during the COVID-19 outbreak. Frontiers in Public Health 2022;10 View
  3. Yoda T, Suksatit B, Tokuda M, Katsuyama H. The Relationship between Sources of COVID-19 Vaccine Information and Willingness to Be Vaccinated: An Internet-Based Cross-Sectional Study in Japan. Vaccines 2022;10(7):1041 View
  4. Zhao S, Hu S, Zhou X, Song S, Wang Q, Zheng H, Zhang Y, Hou Z. The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review. JMIR Public Health and Surveillance 2023;9:e40201 View
  5. Liu H, Chen Q, Evans R. How Official Social Media Affected the Infodemic among Adults during the First Wave of COVID-19 in China. International Journal of Environmental Research and Public Health 2022;19(11):6751 View
  6. Su Y, Lee D, Xiao X. “I enjoy thinking critically, and I'm in control”: Examining the influences of media literacy factors on misperceptions amidst the COVID-19 infodemic. Computers in Human Behavior 2022;128:107111 View
  7. Huang Q, Wei L. Explaining education-based difference in systematic processing of COVID-19 information: Insights into global recovery from infodemic. Information Processing & Management 2022;59(4):102989 View
  8. Hu M, Conway M. Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia. JMIR Infodemiology 2022;2(2):e36941 View
  9. Kreps S, George J, Watson N, Cai G, Ding K. (Mis)Information on Digital Platforms: Quantitative and Qualitative Analysis of Content From Twitter and Sina Weibo in the COVID-19 Pandemic. JMIR Infodemiology 2022;2(1):e31793 View
  10. Bottemanne H. Théories du complot et COVID-19 : comment naissent les croyances complotistes ?. L'Encéphale 2022;48(5):571 View
  11. Reisz D, Crișan I. Perspectives on Mass Media and Governmental Measures during the 2020 COVID-19 Pandemic in a Romanian Sample of Healthcare Practitioners. Healthcare 2022;10(2):191 View
  12. Sun S, Liu Z, Zhai Y, Wang F. COVID-19 Vaccines on TikTok: A Big-Data Analysis of Entangled Discourses. International Journal of Environmental Research and Public Health 2022;19(20):13287 View
  13. Xu W, Tshimula J, Dubé È, Graham J, Greyson D, MacDonald N, Meyer S. Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster–Based BERT Topic Modeling Approach. JMIR Infodemiology 2022;2(2):e41198 View
  14. Song C, Yin H, Shi X, Xie M, Yang S, Zhou J, Wang X, Tang Z, Yang Y, Pan J. Spatiotemporal disparities in regional public risk perception of COVID-19 using Bayesian Spatiotemporally Varying Coefficients (STVC) series models across Chinese cities. International Journal of Disaster Risk Reduction 2022;77:103078 View
  15. Li Z, Wang M, Zhong J, Ren Y. Improving the Communication and Credibility of Government Media in Response to Public Health Emergencies: Analysis of Tweets From the WeChat Official Accounts of 10 Chinese Health Commissioners. Frontiers in Public Health 2022;10 View
  16. Zhu Y, Qian P, Su F, Xu J. WeChat users’ debunking strategies in response to COVID-19 conspiracy theories: A mixed-methods study. Convergence: The International Journal of Research into New Media Technologies 2022;28(4):1060 View
  17. Zhou Y, Xu J, Yin M, Zeng J, Ming H, Wang Y. Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis. International Journal of Environmental Research and Public Health 2022;19(18):11306 View
  18. Charbonneau E, Mellouli S, Chouikh A, Couture L, Desroches S. The Information Sharing Behaviors of Dietitians and Twitter Users in the Nutrition and COVID-19 Infodemic: Content Analysis Study of Tweets. JMIR Infodemiology 2022;2(2):e38573 View
  19. Gao H, Yin H, Peng L, Wang H. Effectiveness of Social Video Platforms in Promoting COVID-19 Vaccination Among Youth: A Content-Specific Analysis of COVID-19 Vaccination Topic Videos on Bilibili. Risk Management and Healthcare Policy 2022;Volume 15:1621 View
  20. Wu Y, Mustafa H. Exploring the impact of social media exposure patterns on people’s belief in fake news during COVID-19: A cross-gender study. Online Journal of Communication and Media Technologies 2023;13(3):e202326 View
  21. Wu X, Li Z, Xu L, Li P, Liu M, Huang C. COVID-19 Vaccine–Related Information on the WeChat Public Platform: Topic Modeling and Content Analysis. Journal of Medical Internet Research 2023;25:e45051 View
  22. Zheng H, Wang X, Huang Y. Fake news in a time of plague: Exploring individuals’ online information management in the COVID-19 era. Computers in Human Behavior 2023;146:107790 View
  23. Li L, Bui Q, Yan H. The impact of COVID-19 information overload on Vietnamese consumers' online purchase intention. International Journal of Emerging Markets 2023 View
  24. Ng J, Liu S, Maini I, Pereira W, Cramer H, Moher D. Complementary, alternative, and integrative medicine-specific COVID-19 misinformation on social media: A scoping review. Integrative Medicine Research 2023;12(3):100975 View
  25. Tao R, Li J, Shen L, Yang S. Hope over fear: The interplay between threat information and hope appeal corrections in debunking early COVID-19 misinformation. Social Science & Medicine 2023;333:116132 View
  26. Nan X, Thier K, Wang Y. Health misinformation: what it is, why people believe it, how to counter it. Annals of the International Communication Association 2023;47(4):381 View
  27. Yeung A, Dirisanala S, Abraham A, Huang J, Brennan G, Urrutia M, Baran J, Nguyen K, Xu N, Shang T, Zhang J, Klonoff D, Davis G, Pasquel F. Diabetes Research and Resource Sharing During the COVID-19 Pandemic: A Systematic Review and Experience from an Academic/Non-Profit Resource Website. Journal of Diabetes Science and Technology 2023;17(5):1284 View
  28. Zhu R, Zhang X. Public sector’s misinformation debunking during the public health campaign: a case of Hong Kong. Health Promotion International 2023;38(3) View
  29. Rukasha I. The Double-Edged Sword Effect of Social Media on COVID-19 in Sub-Saharan Africa. Commonwealth Youth and Development 2023;20(1) View
  30. He M, Li S, Geng Y. Teachers’ Experiences of Keeping Special Education Students Informed of the COVID-19 Pandemic: A Qualitative Study. Education Research International 2023;2023:1 View
  31. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  32. Zhang S, Zhang Y, Li J, Ni Z, Liu Z. Heart or mind? The impact of congruence on the persuasiveness of cognitive versus affective appeals in debunking messages on social media during public health crises. Computers in Human Behavior 2024;154:108136 View
  33. Tie B, Yang X, Qiu J. Validation of the Appearance-Related Social Media Consciousness Scale with Chinese adolescents and young adults. Body Image 2024;48:101677 View
  34. Su Z, McDonnell D, Cheshmehzangi A, Bentley B, Šegalo S, da Veiga C, Xiang Y. Where should “Humans” be in “One Health”? Lessons from COVID-19 for One Health. Globalization and Health 2024;20(1) View
  35. Marsall M, Dinse H, Schröder J, Skoda E, Teufel M, Bäuerle A. Assessing Electronic Health Literacy in Individuals With the Post–COVID-19 Condition Using the German Revised eHealth Literacy Scale: Validation Study. JMIR Formative Research 2024;8:e52189 View
  36. Zhang S, Zhou H, Zhu Y. Have we found a solution for health misinformation? A ten-year systematic review of health misinformation literature 2013–2022. International Journal of Medical Informatics 2024;188:105478 View

Books/Policy Documents

  1. Andriano-Moore S, Cai Y. Coping with COVID-19, the Mobile Way. View
  2. Zhang S, Meng J, Huang R. Coping with COVID-19, the Mobile Way. View
  3. Su Z. Handbook of Cancer and Immunology. View
  4. Xu H, Curci M, Ek S, Liu P, Li Z, Xu S. Cloud Computing – CLOUD 2021. View