ArticleVaccine2023
Public discourse and debate about vaccines in the midst of the covid-19 pandemic: A qualitative content analysis of Twitter.
Article in Vaccine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Understanding Vaccine Hesitancy in Louisiana Through Social Media Listening and Community Feedback: Cross-Sectional Study.JMIR infodemiology · 2026Article
- A thematic analysis of UK COVID-19 vaccine hesitancy discussions on Twitter.BMC public health · 2025Article
- Community Level Correlates of COVID-19 Booster Vaccine Hesitancy in the United States: A Cross-Sectional Analysis.Vaccines · 2024Article
- Readiness for influenza and COVID-19 vaccination in Germany: a comparative analysis.Frontiers in psychology · 2024Article
- Aminoacyl-tRNA synthetase interactions in SARS-CoV-2 infection.Biochemical Society transactions · 2023Review
- Article
- COVID-19 Response of the JournalPublic health reports (Washington, D.C. : 1974)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesCharacterize the public debate and discourse about vaccines during the covid-19 vaccination programmes.
methodsWe performed a manual content analysis of a sample of English-written Twitter posts that included the word vaccine and its derivatives. We categorized 7 variables pertaining to the content of the posts, and classified the type of user that published the post and the number of retweets. Then, the patterns of association between these variables were further explored.
resultsAmong the tweets with negative tone towards vaccines, 33% display negationist discourses, 29% protest or defiance discourses, 13% discuss the pandemic management measures and yet another 13% of these tweets display a scientific discourse. Research results, vaccination data and practical information are more associated to positive tone towards vaccines, while news relate to neutral tone. The users that received more retweets were media accounts and journalists, followed by government accounts and scientific organizations related to the government. Tweets displaying preventive messages received more retweets in average. The discourses most associated with objective information are the preventive, institutional, medical-scientific, and those about the different measures to manage the pandemic. On the other hand, the most subjective tweets are those with negationist, antinegationist and protest discourses.
conclusionsAlthough there is a non-negligible proportion of tweets that are directly opposed to vaccines, also an important part of vaccine-negative content takes the form of protest discourses, criticisms towards government actions as well as towards the measures to tackle the pandemic. Therefore, negative discourses during the pandemic included serious vaccine hesitancy cases. Moreover, they were not only fuelled by distrust in science, but also and very importantly they were connected to dissatisfaction towards the public management of the pandemic.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.