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

Misinformation and Disinformation Outbreaks and Information Prevalence Studies (33) JMIR Theme Issue: COVID-19 Special Issue (2275) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1402) Outbreak and Pandemic Preparedness and Management (1555) Infectious Diseases (non-STD/STI) (1323) Infodemiology and Infoveillance (1166) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (946)

Published on in Vol 2, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32378, first published .
Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale

Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale

Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale

Authors of this article:

Emily Chen 1, 2 Author Orcid Image ;   Julie Jiang 1, 2 Author Orcid Image ;   Ho-Chun Herbert Chang 3 Author Orcid Image ;   Goran Muric 1 Author Orcid Image ;   Emilio Ferrara 1, 2, 3, 4 Author Orcid Image
Article Authors Cited by (15) Tweetations (37) Metrics

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  1. Bhat S, Gadiyar A. Attitude of the Dental Undergraduate Students and Interns towards Dentistry Post COVID-19. Journal of Health and Allied Sciences NU 2023;13(03):400 View
  2. Jiang H, Castellanos A, Castillo A, Gomes P, Li J, VanderMeer D. Nurses’ Work Concerns and Disenchantment During the COVID-19 Pandemic: Machine Learning Analysis of Web-Based Discussions. JMIR Nursing 2023;6:e40676 View
  3. Pierri F, DeVerna M, Yang K, Axelrod D, Bryden J, Menczer F. One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study. Journal of Medical Internet Research 2023;25:e42227 View
  4. Niu Q, Liu J, Kato M, Shinohara Y, Matsumura N, Aoyama T, Nagai-Tanima M. Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis. JMIR Infodemiology 2022;2(1):e32335 View
  5. Mackey T, Baur C, Eysenbach G. Advancing Infodemiology in a Digital Intensive Era. JMIR Infodemiology 2022;2(1):e37115 View
  6. Huang Q, Mao B, Jia X, Peng W. COVID-19 Information Overload Mediated the Effects of Cross-Channel Information Differences on Health Information Elaboration. Journal of Health Communication 2023;28(7):401 View
  7. Xia X, Zhang Y, Jiang W, Wu C. Staying Home, Tweeting Hope: Mixed Methods Study of Twitter Sentiment Geographical Index During US Stay-At-Home Orders. Journal of Medical Internet Research 2023;25:e45757 View
  8. Isip Tan I, Cleofas J, Solano G, Pillejera J, Catapang J. Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study. JMIR Formative Research 2023;7:e41134 View
  9. Bacon E, An L, Yang P, Hawley S, Van Horn M, Resnicow K. Novel Psychosocial Correlates of COVID-19 Vaccine Hesitancy: Cross-Sectional Survey. JMIR Formative Research 2023;7:e45980 View
  10. Broughton Micova S, Calef A. Elements for Effective Systemic Risk Assessment Under the DSA. SSRN Electronic Journal 2023 View
  11. Pierri F, Luceri L, Chen E, Ferrara E. How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events. EPJ Data Science 2023;12(1) View
  12. Tai Y, Buma R, Desmarais B. Official yet questionable: examining misinformation in U.S. state legislators’ tweets. Journal of Information Technology & Politics 2023:1 View
  13. Chang H, Pham B, Ferrara E. Parasocial diffusion: K-pop fandoms help drive COVID-19 public health messaging on social media. Online Social Networks and Media 2023;37-38:100267 View