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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Mass Media/Social Media Communication and Campaigns (461) JMIR Theme Issue: COVID-19 Special Issue (2452) Outbreak and Pandemic Preparedness and Management (1727) Quality/Credibility of eHealth Information and Trust Issues (531)

Published on in Vol 7, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26527, first published .
“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Authors of this article:

Dax Gerts1 Author Orcid Image ;   Courtney D Shelley1 Author Orcid Image ;   Nidhi Parikh1 Author Orcid Image ;   Travis Pitts1 Author Orcid Image ;   Chrysm Watson Ross1, 2 Author Orcid Image ;   Geoffrey Fairchild1 Author Orcid Image ;   Nidia Yadria Vaquera Chavez1, 2 Author Orcid Image ;   Ashlynn R Daughton1 Author Orcid Image
Article Authors Cited by (55) Tweetations (36) Metrics

Journals

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  9. Alamoodi A, Zaidan B, Al-Masawa M, Taresh S, Noman S, Ahmaro I, Garfan S, Chen J, Ahmed M, Zaidan A, Albahri O, Aickelin U, Thamir N, Fadhil J, Salahaldin A. Multi-perspectives systematic review on the applications of sentiment analysis for vaccine hesitancy. Computers in Biology and Medicine 2021;139:104957 View
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  20. Ravichandran B, Keikhosrokiani P. Classification of Covid-19 misinformation on social media based on neuro-fuzzy and neural network: A systematic review. Neural Computing and Applications 2023;35(1):699 View
  21. Ginossar T, Cruickshank I, Zheleva E, Sulskis J, Berger-Wolf T. Cross-platform spread: vaccine-related content, sources, and conspiracy theories in YouTube videos shared in early Twitter COVID-19 conversations. Human Vaccines & Immunotherapeutics 2022;18(1):1 View
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  24. Liu X, Alsghaier H, Tong L, Ataullah A, McRoy S. Visualizing the Interpretation of a Criteria-Driven System That Automatically Evaluates the Quality of Health News: Exploratory Study of 2 Approaches. JMIR AI 2022;1(1):e37751 View
  25. Kim S, Chen K. The use of emotions in conspiracy and debunking videos to engage publics on YouTube. New Media & Society 2024;26(7):3854 View
  26. Meuer M, Oeberst A, Imhoff R. How do conspiratorial explanations differ from non‐conspiratorial explanations? A content analysis of real‐world online articles. European Journal of Social Psychology 2023;53(2):288 View
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  28. Lee J, Hameleers M, Shin S. The emotional effects of multimodal disinformation: How multimodality, issue relevance, and anxiety affect misperceptions about the flu vaccine. New Media & Society 2024;26(12):6838 View
  29. Oyeyemi S, Fagbemi S, Busari I, Wynn R. Belief in COVID-19 Conspiracy Theories, Level of Trust in Government Information, and Willingness to Take COVID-19 Vaccines Among Health Care Workers in Nigeria: Survey Study. JMIR Formative Research 2023;7:e41925 View
  30. Li B, Ji D, Fu M, Tan C, Chong A, Lim E. Unveiling the formation of conspiracy theory on social media: A discourse analysis. Journal of Information Technology 2024;39(3):392 View
  31. 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
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