ArticleJournal of medical Internet research2023
One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Longitudinal predictors of vaccine conspiracy beliefs: findings from a five-wave panel study in Japan.Scientific reports · 2026Article
- Social Contagion in COVID-19 Discussions Within the Belgian Reddit Community: Statistical and Modeling Study.Journal of medical Internet research · 2026Article
- Article
- Engagement Trends in Online Vaccine Content: Longitudinal YouTube Study.Journal of medical Internet research · 2026Article
- Auditing the impact of social media's policy shift on anti-vaccine discourse: A large language model-driven empirical study.PloS one · 2026Article
- Perceptions of health misinformation on social media: patterns and predictors.Frontiers in medicine · 2026Article
- Social Media Metrics and Popular Legitimacy: Content Analysis of Pre- and Post-COVID-19 Public Engagement With the World Health Organization on X.Journal of medical Internet research · 2025Article
- Willingness among adults in the United States to receive a combination influenza and COVID-19 vaccine.Human vaccines & immunotherapeutics · 2025Article
- Digital Divide or Educational Divide? The Impact of Social Media on COVID-19 Vaccination in Middle-Aged and Older Adults.medRxiv : the preprint server for health sciences · 2025Article
- Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.Research square · 2025Article
- Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.Journal of medical Internet research · 2025Article
- Only the Bluesky is the limit: ten tips for a trending #Skytorial.Clinical kidney journal · 2025Review
- Mapping global public perspectives on mRNA vaccines and therapeutics.NPJ vaccines · 2024Article
- COVID-19 and influenza vaccine uptake in women with criminal-legal system involvement.Vaccine · 2024Article
- Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making.Drug safety · 2024Article
- Article
- Identification, analysis and prediction of valid and false information related to vaccines from Romanian tweets.Frontiers in public health · 2024Article
- Twitter Misinformation Discourses About Vaping: Systematic Content Analysis.Journal of medical Internet research · 2023Article
- Assessment of the Early Detection of Anosmia and Ageusia Symptoms in COVID-19 on Twitter: Retrospective Study.JMIR infodemiology · 2023Article
- Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVaccinations play a critical role in mitigating the impact of COVID-19 and other diseases. Past research has linked misinformation to increased hesitancy and lower vaccination rates. Gaps remain in our knowledge about the main drivers of vaccine misinformation on social media and effective ways to intervene.
objectiveOur longitudinal study had two primary objectives: (1) to investigate the patterns of prevalence and contagion of COVID-19 vaccine misinformation on Twitter in 2021, and (2) to identify the main spreaders of vaccine misinformation. Given our initial results, we further considered the likely drivers of misinformation and its spread, providing insights for potential interventions.
methodsWe collected almost 300 million English-language tweets related to COVID-19 vaccines using a list of over 80 relevant keywords over a period of 12 months. We then extracted and labeled news articles at the source level based on third-party lists of low-credibility and mainstream news sources, and measured the prevalence of different kinds of information. We also considered suspicious YouTube videos shared on Twitter. We focused our analysis of vaccine misinformation spreaders on verified and automated Twitter accounts.
resultsOur findings showed a relatively low prevalence of low-credibility information compared to the entirety of mainstream news. However, the most popular low-credibility sources had reshare volumes comparable to those of many mainstream sources, and had larger volumes than those of authoritative sources such as the US Centers for Disease Control and Prevention and the World Health Organization. Throughout the year, we observed an increasing trend in the prevalence of low-credibility news about vaccines. We also observed a considerable amount of suspicious YouTube videos shared on Twitter. Tweets by a small group of approximately 800 "superspreaders" verified by Twitter accounted for approximately 35% of all reshares of misinformation on an average day, with the top superspreader (@RobertKennedyJr) responsible for over 13% of retweets. Finally, low-credibility news and suspicious YouTube videos were more likely to be shared by automated accounts.
conclusionsThe wide spread of misinformation around COVID-19 vaccines on Twitter during 2021 shows that there was an audience for this type of content. Our findings are also consistent with the hypothesis that superspreaders are driven by financial incentives that allow them to profit from health misinformation. Despite high-profile cases of deplatformed misinformation superspreaders, our results show that in 2021, a few individuals still played an outsized role in the spread of low-credibility vaccine content. As a result, social media moderation efforts would be better served by focusing on reducing the online visibility of repeat spreaders of harmful content, especially during public health crises.
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