Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19629, first published .
Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

Journals

  1. Chandrasekaran R, Mehta V, Valkunde T, Moustakas E. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e22624 View
  2. Lyu J, Luli G. Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study. Journal of Medical Internet Research 2021;23(2):e25108 View
  3. Wang H, Li Y, Hutch M, Naidech A, Luo Y. Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study. Journal of Medical Internet Research 2021;23(2):e26302 View
  4. Waggoner P. Community Detection in Google Searches Related to “Coronavirus”. Journal of Data Science 2021:334 View
  5. González L, Devís-Devís J, Pellicer-Chenoll M, Pans M, Pardo-Ibañez A, García-Massó X, Peset F, Garzón-Farinós F, Pérez-Samaniego V. The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis. International Journal of Environmental Research and Public Health 2021;18(9):4554 View
  6. Motahari-Nezhad H, Shekofteh M, Andalib-Kondori M. Social media as a platform for information and support for coronavirus: analysis ofCOVID-19 Facebook groups. Global Knowledge, Memory and Communication 2022;71(8/9):772 View
  7. Jing F, Li Z, Qiao S, Zhang J, Olatosi B, Li X. Using geospatial social media data for infectious disease studies: a systematic review. International Journal of Digital Earth 2023;16(1):130 View
  8. Esteves-Pereira M, Ferreira D, Fontes-Carvalho R, Guerreiro C, Oliveira-Santos M, Ladeiras-Lopes R. Social media use by cardiovascular healthcare professionals in Portugal. Revista Portuguesa de Cardiologia 2023;42(4):349 View
  9. Heyerdahl L, Lana B, Giles-Vernick T. The Impact of the Online COVID-19 Infodemic on French Red Cross Actors’ Field Engagement and Protective Behaviors: Mixed Methods Study. JMIR Infodemiology 2021;1(1):e27472 View
  10. Lane J, Habib D, Curtis B. Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data. Journal of Medical Internet Research 2023;25:e39484 View
  11. Li P, Chen B, Deveaux G, Luo Y, Tao W, Li W, Wen J, Zheng Y. Cross-Verification of COVID-19 Information Obtained From Unofficial Social Media Accounts and Associated Changes in Health Behaviors: Web-Based Questionnaire Study Among Chinese Netizens. JMIR Public Health and Surveillance 2022;8(5):e33577 View
  12. Singh P, Kaur S, Baabdullah A, Dwivedi Y, Sharma S, Sawhney R, Das R. Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter. Information Systems Frontiers 2023;25(1):199 View
  13. Staccini P, Lau A. Consumer Informatics and COVID-19 Pandemics: Challenges and Opportunities for Research. Yearbook of Medical Informatics 2021;30(01):210 View
  14. Gunasekeran D, Chew A, Chandrasekar E, Rajendram P, Kandarpa V, Rajendram M, Chia A, Smith H, Leong C. The Impact and Applications of Social Media Platforms for Public Health Responses Before and During the COVID-19 Pandemic: Systematic Literature Review. Journal of Medical Internet Research 2022;24(4):e33680 View
  15. Liu X, Kar B, Montiel Ishino F, Onega T, Williams F. The Associations Between Racially/Ethnically Stratified COVID-19 Tweets and COVID-19 Cases and Deaths: Cross-sectional Study. JMIR Formative Research 2022;6(5):e30371 View
  16. Endo P, Santos G, de Lima Xavier M, Nascimento Campos G, de Lima L, Silva I, Egli A, Lynn T. Illusion of Truth: Analysing and Classifying COVID-19 Fake News in Brazilian Portuguese Language. Big Data and Cognitive Computing 2022;6(2):36 View
  17. Elyashar A, Plochotnikov I, Cohen I, Puzis R, Cohen O. The State of Mind of Health Care Professionals in Light of the COVID-19 Pandemic: Text Analysis Study of Twitter Discourses. Journal of Medical Internet Research 2021;23(10):e30217 View
  18. Barkay O, Binay U, Karakeçili F. Evolution of Public Responses to COVID-19: Comparing Changes in People's Emotions, Behaviors, and Precautions at the Onset and End Stage of the Pandemic. Cureus 2023 View
  19. Mori Y, Miyatake N, Suzuki H, Mori Y, Okada S, Tanimoto K. Comparison of Impressions of COVID-19 Vaccination and Influenza Vaccination in Japan by Analyzing Social Media Using Text Mining. Vaccines 2023;11(8):1327 View
  20. Purwandari K, Perdana R, Sigalingging J, Rahutomo R, Pardamean B. Automatic Smart Crawling on Twitter for Weather Information in Indonesia. Procedia Computer Science 2023;227:795 View
  21. Terry K, Yang F, Yao Q, Liu C. The role of social media in public health crises caused by infectious disease: a scoping review. BMJ Global Health 2023;8(12):e013515 View
  22. Li Y, Zeng Z, Yu L. Withdrawn: The crisis communication of the COVID-19 pandemic in media discourse: Text mining for infectious disease frames and environmental pollution. AQUA — Water Infrastructure, Ecosystems and Society 2024 View

Books/Policy Documents

  1. Bitzer E, Schaefer C. Gesundheitskompetenz. View