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

Theme Issue: The New Digital Normal in Health and Medicine (33) JMIR Theme Issue: COVID-19 Special Issue (2388) Outbreak and Pandemic Preparedness and Management (1673) Mass Media/Social Media Communication and Campaigns (446) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Infodemiology and Infoveillance (1269) Vaccination and Immunization in the Digital Age (343) Quality/Credibility of eHealth Information and Trust Issues (485) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42227, first published .
One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

Authors of this article:

Francesco Pierri1, 2 Author Orcid Image ;   Matthew R DeVerna2 Author Orcid Image ;   Kai-Cheng Yang2 Author Orcid Image ;   David Axelrod2 Author Orcid Image ;   John Bryden2 Author Orcid Image ;   Filippo Menczer2 Author Orcid Image
Article Authors Cited by (17) Tweetations (119) Metrics

Journals

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  2. Ng Q, Ng C, Ong C, Lee D, Liew T. Examining Public Messaging on Influenza Vaccine over Social Media: Unsupervised Deep Learning of 235,261 Twitter Posts from 2017 to 2023. Vaccines 2023;11(10):1518 View
  3. Al-Rawi A, Blackwell B, Zemenchik K, Lee K. Twitter Misinformation Discourses About Vaping: Systematic Content Analysis. Journal of Medical Internet Research 2023;25:e49416 View
  4. Duzen Z, Riveni M, Aktas M. Analyzing the Spread of Misinformation on Social Networks: A Process and Software Architecture for Detection and Analysis. Computers 2023;12(11):232 View
  5. Ahammad T. Identifying hidden patterns of fake COVID-19 news: An in-depth sentiment analysis and topic modeling approach. Natural Language Processing Journal 2024;6:100053 View
  6. Valeanu A, Mihai D, Andrei C, Puscasu C, Ionica A, Hinoveanu M, Predoi V, Bulancea E, Chirita C, Negres S, Marineci C. Identification, analysis and prediction of valid and false information related to vaccines from Romanian tweets. Frontiers in Public Health 2024;12 View
  7. AŞAN H. 6 Şubat 2023 Kahramanmaraş Depremi Sonrası Afet Yönetimi Açısından Sosyal Medya Hesaplarının Güvenirlik Analizi ve Değerlendirilmesi. Akademik Yaklaşımlar Dergisi 2024 View
  8. Wessel D, Pogrebnyakov N. Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making. Drug Safety 2024;47(5):495 View
  9. Fu C, Zhang J, Kang X. True or false? Linguistic and demographic factors influence veracity judgment of COVID-19 rumors. Humanities and Social Sciences Communications 2024;11(1) View
  10. Unlu A, Truong S, Sawhney N, Sivelä J, Tammi T. Long-term assessment of social amplification of risk during COVID-19: challenges to public health agencies amid misinformation and vaccine stance. Journal of Computational Social Science 2024 View
  11. Hong C. Fake news virality: Relational niches and the diffusion of COVID-19 vaccine misinformation. Social Science Research 2024;120:103004 View
  12. Lazarus J, White T, Wyka K, Ratzan S, Rabin K, Larson H, Martinon-Torres F, Kuchar E, Abdool Karim S, Giles-Vernick T, Müller S, Batista C, Myburgh N, Kampmann B, El-Mohandes A. Influence of COVID-19 on trust in routine immunization, health information sources and pandemic preparedness in 23 countries in 2023. Nature Medicine 2024;30(6):1559 View
  13. DeVerna M, Aiyappa R, Pacheco D, Bryden J, Menczer F, Guarino S. Identifying and characterizing superspreaders of low-credibility content on Twitter. PLOS ONE 2024;19(5):e0302201 View
  14. Allen J, Watts D, Rand D. Quantifying the impact of misinformation and vaccine-skeptical content on Facebook. Science 2024;384(6699) View