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

Big Data (220) JMIR Theme Issue: COVID-19 Special Issue (2394) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1484) Outbreak and Pandemic Preparedness and Management (1679) Infectious Diseases (non-STD/STI) (1490) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27116, first published .
Social Media Insights During the COVID-19 Pandemic: Infodemiology Study Using Big Data

Social Media Insights During the COVID-19 Pandemic: Infodemiology Study Using Big Data

Social Media Insights During the COVID-19 Pandemic: Infodemiology Study Using Big Data

Authors of this article:

Huyen Thi Thanh Tran1 Author Orcid Image ;   Shih-Hao Lu1 Author Orcid Image ;   Ha Thi Thu Tran2 Author Orcid Image ;   Bien Van Nguyen3 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Deiner M, Seitzman G, Kaur G, McLeod S, Chodosh J, Lietman T, Porco T. Sustained Reductions in Online Search Interest for Communicable Eye and Other Conditions During the COVID-19 Pandemic: Infodemiology Study. JMIR Infodemiology 2022;2(1):e31732 View
  2. Deiner M, Kaur G, McLeod S, Schallhorn J, Chodosh J, Hwang D, Lietman T, Porco T. A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study. Journal of Medical Internet Research 2022;24(7):e27310 View
  3. Lohiniva A, Sibenberg K, Austero S, Skogberg N. Social Listening to Enhance Access to Appropriate Pandemic Information Among Culturally Diverse Populations: Case Study From Finland. JMIR Infodemiology 2022;2(2):e38343 View
  4. Nguyen P, Tsai J, Lin M, Hu Y. A Hybrid Model with Spherical Fuzzy-AHP, PLS-SEM and ANN to Predict Vaccination Intention against COVID-19. Mathematics 2021;9(23):3075 View
  5. Liu J, Lu C, Lu S. Increase the Number of Views and Shares of COVID-19 Videos: Content Relevance and Emotional Consistency with Virus Variant Topics. Healthcare 2022;11(1):119 View
  6. Lee E, Zheng H, Goh D, Lee C, Theng Y. Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework. Health Communication 2024;39(3):493 View
  7. Yang G, Wang Z, Chen L. Investigating the Public Sentiment in Major Public Emergencies Through the Complex Networks Method: A Case Study of COVID-19 Epidemic. Frontiers in Public Health 2022;10 View
  8. Lohiniva A, Nurzhynska A, Hudi A, Anim B, Aboagye D. Infodemic Management Using Digital Information and Knowledge Cocreation to Address COVID-19 Vaccine Hesitancy: Case Study From Ghana. JMIR Infodemiology 2022;2(2):e37134 View
  9. Lohiniva A, Pensola A, Hyökki S, Sivelä J, Tammi T. COVID-19 risk perception framework of the public: an infodemic tool for future pandemics and epidemics. BMC Public Health 2022;22(1) View
  10. Bucci L, Lamprianou S, Gesualdo F, Tozzi A, Ghalayini T, Sahinovic I, Pal S. A social media intervention for communicating vaccine safety in low- and middle-income countries: protocol for a pilot study. Frontiers in Public Health 2023;11 View
  11. Zhang J, Wang Y, Mouton M, Zhang J, Shi M. Public Discourse, User Reactions, and Conspiracy Theories on the X Platform About HIV Vaccines: Data Mining and Content Analysis. Journal of Medical Internet Research 2024;26:e53375 View

Books/Policy Documents

  1. Batra K, Batra R, Sharma M. Effective Use of Social Media in Public Health. View
  2. Cuyvers J, Passanante A, Pertwee E, Paterson P, Lin L, J. Larson H. Modernizing Global Health Security to Prevent, Detect, and Respond. View