ArticlePloS one2022
Characterizing polarization in online vaccine discourse-A large-scale study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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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
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 93 citations in OpenAlex.
- Drivers of health polarization during the COVID-19 pandemic: A systematic review.Science advances · 2025Pooled it
- Assessment of the Cultural Nuances in COVID-19 Vaccine Uptake Through a Comparative Analysis of English and Spanish Facebook Posts in Tarrant County, Texas: Longitudinal Study.Online journal of public health informatics · 2026Article
- Auditing the impact of social media's policy shift on anti-vaccine discourse: A large language model-driven empirical study.PloS one · 2026Article
- Leveraging complex network features improves vaccine stance classification.Scientific reports · 2025Article
- Information Pathways and Voids in Critical German Online Communities During the COVID-19 Vaccination Discourse: Cross-Platform and Mixed Methods Analysis.Journal of medical Internet research · 2025Article
- Vaccination Conversations on X in Spanish and Catalan: Qualitative Content Analysis.JMIR infodemiology · 2025Article
- The Evolution of Monkeypox Vaccination Acceptance in Romania: A Comparative Analysis (2022-2025), Psychosocial Perceptions, and the Impact of Anti-Vaccination Rhetoric on Societal Security.Behavioral sciences (Basel, Switzerland) · 2025Article
- Exploring Vaccine Hesitancy in the Philippines: A Content Analysis of Comments on National TV Channel YouTube Videos.International journal of environmental research and public health · 2025Article
- Twitter communities are associated with changing user's opinion towards COVID-19 vaccine in Japan.Scientific reports · 2025Article
- Public Health Advocacy in Times of Pandemic: An Analysis of the Medicare-For-All Debate on Twitter During COVID-19.Behavioral sciences (Basel, Switzerland) · 2025Article
- Modelling the mitigation of anti-vaccine opinion propagation to suppress epidemic spread: A computational approach.PloS one · 2025Article
- Public agreement with misinformation about wind farms.Nature communications · 2024Article
- Vaccine Hesitancy in Taiwan: Temporal, Multilayer Network Study of Echo Chambers Shaped by Influential Users.Online journal of public health informatics · 2024Article
- How older adults manage misinformation and information overload - A qualitative study.BMC public health · 2024Article
- Political context of the European vaccine debate on Twitter.Scientific reports · 2024Article
- Article
- Analyzing information sharing behaviors during stance formation on COVID-19 vaccination among Japanese Twitter users.PloS one · 2024Article
- Article
- Recruiting a Hard-to-Reach, Hidden and Vulnerable Population: The Methodological and Practical Pitfalls of Researching Vaccine-Hesitant Parents.Qualitative health research · 2023Article
- COVID-19 and social media: Beyond polarization.PNAS nexus · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Vaccine hesitancy is currently recognized by the WHO as a major threat to global health. Recently, especially during the COVID-19 pandemic, there has been a growing interest in the role of social media in the propagation of false information and fringe narratives regarding vaccination. Using a sample of approximately 60 billion tweets, we conduct a large-scale analysis of the vaccine discourse on Twitter. We use methods from deep learning and transfer learning to estimate the vaccine sentiments expressed in tweets, then categorize individual-level user attitude towards vaccines. Drawing on an interaction graph representing mutual interactions between users, we analyze the interplay between vaccine stances, interaction network, and the information sources shared by users in vaccine-related contexts. We find that strongly anti-vaccine users frequently share content from sources of a commercial nature; typically sources which sell alternative health products for profit. An interesting aspect of this finding is that concerns regarding commercial conflicts of interests are often cited as one of the major factors in vaccine hesitancy. Further, we show that the debate is highly polarized, in the sense that users with similar stances on vaccination interact preferentially with one another. Extending this insight, we provide evidence of an epistemic echo chamber effect, where users are exposed to highly dissimilar sources of vaccine information, depending the vaccination stance of their contacts. Our findings highlight the importance of understanding and addressing vaccine mis- and dis-information in the context in which they are disseminated in social networks.
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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.