This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2458) Infodemiology and Infoveillance (1365) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1049) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19788, first published .
Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study

Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study

Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study

Authors of this article:

Atina Husnayain1, 2 Author Orcid Image ;   Eunha Shim3 Author Orcid Image ;   Anis Fuad2 Author Orcid Image ;   Emily Chia-Yu Su1, 4, 5 Author Orcid Image
Article Authors Cited by (28) Tweetations (2) Metrics

Journals

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  8. Husnayain A, Chuang T, Fuad A, Su E. High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA. International Journal of Infectious Diseases 2021;109:269 View
  9. Kim S, Lim S, Kim S. Real-time analysis and predictability of the health functional food market using big data. Food Science and Biotechnology 2021;30(13):1667 View
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  11. Montesi M. Human information behavior during the Covid-19 health crisis. A literature review. Library & Information Science Research 2021;43(4):101122 View
  12. Saegner T, Austys D. Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review. International Journal of Environmental Research and Public Health 2022;19(19):12394 View
  13. Kłak A, Grygielska J, Mańczak M, Ejchman-Pac E, Owoc J, Religioni U, Olszewski R. Online Information of COVID-19: Visibility and Characterization of Highest Positioned Websites by Google between March and April 2020—A Cross-Country Analysis. International Journal of Environmental Research and Public Health 2022;19(3):1491 View
  14. An L, Russell D, Mihalcea R, Bacon E, Huffman S, Resnicow K. Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study. JMIR Infodemiology 2021;1(1):e32127 View
  15. 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
  16. Husnayain A, Shim E, Fuad A, Su E. Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study. Journal of Medical Internet Research 2021;23(12):e34178 View
  17. Htay M, Parial L, Tolabing M, Dadaczynski K, Okan O, Leung A, Su T, Padhi B. Digital health literacy, online information-seeking behaviour, and satisfaction of Covid-19 information among the university students of East and South-East Asia. PLOS ONE 2022;17(4):e0266276 View
  18. Lee J. The Gendered Outbreak of COVID-19 in South Korea. Feminist Economics 2022;28(4):89 View
  19. Montesi M. Everyday information behavior during the “new normal” of the Covid-19 pandemic: approaching the notions of experiential and local knowledge. Journal of Documentation 2023;79(1):160 View
  20. 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
  21. Hwang J. Subjective Changes in Tobacco Product Use among Korean Adults during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2022;19(6):3272 View
  22. Ming W, Huang F, Chen Q, Liang B, Jiao A, Liu T, Wu H, Akinwunmi B, Li J, Liu G, Zhang C, Huang J, Liu Q. Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries. JMIR Public Health and Surveillance 2021;7(12):e26644 View
  23. Kim C, Kim Y, Heo N, Park E, Choi S, Jang S, Kim N, Kwon D, Park Y, Choi B, Ha B, Jung K, Park C, Park S, Lee H. COVID-19 outbreak in a military unit in Korea. Epidemiology and Health 2021;43:e2021065 View
  24. Chekar C, Kim H. COVID-19 Exceptionalism: Explaining South Korean Responses. East Asian Science, Technology and Society: An International Journal 2022;16(1):7 View
  25. Zayed B, Talaia A, Gaaboobah M, Amer S, Mansour F. Google Trends as a predictive tool in the era of COVID-19: a scoping review. Postgraduate Medical Journal 2023;99(1175):962 View
  26. Yin J, Lui J. Factors influencing risk perception during Public Health Emergencies of International Concern (PHEIC): a scoping review. BMC Public Health 2024;24(1) View
  27. Ahn S, Yim K, Won H, Kim K, Jeong D. Discovering Time-Varying Public Interest for COVID-19 Case Prediction in South Korea Using Search Engine Queries: Infodemiology Study (Preprint). Journal of Medical Internet Research 2024 View
  28. Ma M. Computational Analysis of Linguistic Markers Reveals Group Identification Patterns During a Global Public Health Crisis. Social and Personality Psychology Compass 2024;18(11) View