Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23272, first published .
COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication

COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication

COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication

Journals

  1. Lee K, Kim B, Nan D, Kim J. Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data. International Journal of Environmental Research and Public Health 2021;18(12):6432 View
  2. DePaula N, Hagen L, Roytman S, Alnahass D. Platform Effects on Public Health Communication: A Comparative and National Study of Message Design and Audience Engagement Across Twitter and Facebook. JMIR Infodemiology 2022;2(2):e40198 View
  3. Moon H, Lee G, Cho Y. Readability of Korean-Language COVID-19 Information from the South Korean National COVID-19 Portal Intended for the General Public: Cross-sectional Infodemiology Study. JMIR Formative Research 2022;6(3):e30085 View
  4. Shin Y, Seo H, Lee S, Jang Y, Kim H. South Korean government’s risk communication during the COVID-19 pandemic crisis: Lessons learned and policy recommendations. Korean Journal of Health Education and Promotion 2021;38(4):63 View
  5. Chin H, Lima G, Shin M, Zhunis A, Cha C, Choi J, Cha M. User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2023;25:e40922 View
  6. Sharma A, Khosla K, Potharaju K, Mukherjea A, Sarkar U. COVID-19–Associated Misinformation Across the South Asian Diaspora: Qualitative Study of WhatsApp Messages. JMIR Infodemiology 2023;3:e38607 View
  7. Imran M, Qazi U, Ofli F. TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels. Data 2022;7(1):8 View
  8. Gomes Ferreira C, Murai F, Silva A, Trevisan M, Vassio L, Drago I, Mellia M, Almeida J, Cherifi H. On network backbone extraction for modeling online collective behavior. PLOS ONE 2022;17(9):e0274218 View
  9. Gesser-Edelsburg A. How to Make Health and Risk Communication on Social Media More “Social” During COVID-19. Risk Management and Healthcare Policy 2021;Volume 14:3523 View
  10. Yuan Y, Pang N. Measuring the Evolution of Risk Communication Strategy for Health Authorities During the COVID-19 Pandemic: An Empirical Comparison Between China and the United States. International Journal of Public Health 2022;67 View
  11. Slavik C, Yiannakoulias N, Buttle C, Darlington J. ‘Vaccinfluencers’: a study of influential voices criticizing COVID-19 vaccination efforts and negative vaccine information discourse on Twitter. The Communication Review 2023;26(3):300 View
  12. Zhou J, Sheppard-Law S, Xiao C, Smith J, Lamb A, Axisa C, Chen F. Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic. Health Information Science and Systems 2023;11(1) View
  13. Díaz-Lucena A, Hidalgo-Cobo P. Verification Agencies on TikTok: The Case of MediaWise and Politifact. Societies 2024;14(5):59 View

Books/Policy Documents

  1. Dhir K, Singh P, Dwivedi Y, Sawhney S, Sawhney R. Co-creating for Context in the Transfer and Diffusion of IT. View
  2. Taqwa Sihidi I, Salahudin , Roziqin A, Kurniawan D. Social Computing and Social Media: Design, User Experience and Impact. View
  3. Akbar P, Nurmandi A, Irawan B, Qodir Z, Juba H. HCI International 2022 Posters. View