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

Vaccination Sentiment and Anti-Vaccination Infodemiology (61) COVID-19 Vaccination (153) JMIR Theme Issue: COVID-19 Special Issue (2458) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Outbreak and Pandemic Preparedness and Management (1740) Infectious Diseases (non-STD/STI) (1588) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (47) Infoveillance and Social Listening (212) Infodemiology and Infoveillance (1365) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1049)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33587, first published .
Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study

Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study

Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study

Authors of this article:

Alec J Calac1, 2 Author Orcid Image ;   Michael R Haupt2, 3 Author Orcid Image ;   Zhuoran Li2, 4, 5 Author Orcid Image ;   Tim Mackey2, 4, 6 Author Orcid Image
Article Authors Cited by (10) Tweetations (18) Metrics

Journals

  1. Zhao S, Hu S, Zhou X, Song S, Wang Q, Zheng H, Zhang Y, Hou Z. The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review. JMIR Public Health and Surveillance 2023;9:e40201 View
  2. Corinti F, Pontillo D, Giansanti D. COVID-19 and the Infodemic: An Overview of the Role and Impact of Social Media, the Evolution of Medical Knowledge, and Emerging Problems. Healthcare 2022;10(4):732 View
  3. Ackleh-Tingle J, Jordan N, Onwubiko U, Chandra C, Harton P, Rentmeester S, Chamberlain A. Prevalence and Correlates of COVID-19 Vaccine Information on Family Medicine Practices’ Websites in the United States: Cross-sectional Website Content Analysis. JMIR Formative Research 2022;6(11):e38425 View
  4. Kwon S, Park A. Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects. Computers in Human Behavior 2023;144:107734 View
  5. Honcharov V, Li J, Sierra M, Rivadeneira N, Olazo K, Nguyen T, Mackey T, Sarkar U. Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis. JMIR Infodemiology 2023;3:e40575 View
  6. Machado Júnior C, Mantovani D, de Sandes-Guimarães L, Romeiro M, Furlaneto C, Bazanini R. Volatility of the COVID-19 vaccine hesitancy: sentiment analysis conducted in Brazil. Frontiers in Public Health 2023;11 View
  7. Barrière J, Frank F, Besancon L, Samuel A, Saada V, Billy E, Al-Ahmad A, Florens N, Seitz-Polski B, Robert J. Letter to Editor “Innate immune suppression by SARS-CoV-2 mRNA vaccinations: The role of G-quadruplexes, exosomes, and MicroRNAs”: Important concerns on the validity of this article. Food and Chemical Toxicology 2023;178:113897 View
  8. Khan S, Biswas M, Shah Z. Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review. Human Vaccines & Immunotherapeutics 2023;19(3) View
  9. Suarez-Lledo V, Ortega-Martin E, Carretero-Bravo J, Ramos-Fiol B, Alvarez-Galvez J. Unraveling the use of disinformation hashtags by social bots during the Covid-19 pandemic: a networks analysis and community detection (Preprint). JMIR Infodemiology 2023 View
  10. Deiner M, Honcharov V, Li J, Mackey T, Porco T, Sarkar U. Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study. JMIR Infodemiology 2024;4:e59641 View