ArticleComputers & security2022
Misinformation warnings: Twitter's soft moderation effects on COVID-19 vaccine belief echoes.
Article in Computers & security, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 103 citations in OpenAlex.
- The Prevalence, Features, Influencing Factors, and Solutions for COVID-19 Vaccine Misinformation: Systematic Review.JMIR public health and surveillance · 2023Pooled it
- Impact of Artificial Intelligence-Generated Content Labels On Perceived Accuracy, Message Credibility, and Sharing Intentions for Misinformation: Web-Based, Randomized, Controlled Experiment.JMIR formative research · 2024Trial
- Disinformation elicits learning biases.eLife · 2026Article
- Labeling AI-generated media online.PNAS nexus · 2025Article
- Unraveling the Use of Disinformation Hashtags by Social Bots During the COVID-19 Pandemic: Social Networks Analysis.JMIR infodemiology · 2025Article
- A thematic analysis of UK COVID-19 vaccine hesitancy discussions on Twitter.BMC public health · 2025Article
- Fact-checker warning labels are effective even for those who distrust fact-checkers.Nature human behaviour · 2024Article
- Improving Social Bot Detection Through Aid and Training.Human factors · 2024Article
- Vaccine Hesitancy in Taiwan: Temporal, Multilayer Network Study of Echo Chambers Shaped by Influential Users.Online journal of public health informatics · 2024Article
- Facebook's shared articles on HPV vaccination: analysis of persuasive strategies.BMC public health · 2024Article
- How denialist amplification spread COVID misinformation and undermined the credibility of public health science.Journal of public health policy · 2024Review
- The Role of Social Media in Knowledge, Perceptions, and Self-Reported Adherence Toward COVID-19 Prevention Guidelines: Cross-Sectional Study.JMIR infodemiology · 2024Article
- Deepfake detection with and without content warnings.Royal Society open science · 2023Article
- An investigation of social media labeling decisions preceding the 2020 U.S. election.PloS one · 2023Article
- Long-term impacts of COVID-19 pandemic on travel behaviour.Travel behaviour & society · 2023Article
- Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis.JMIR infodemiology · 2023Article
- Authority Brings Responsibility: Feedback from Experts Promotes an Overweighting of Health-Related Pseudoscientific Beliefs.International journal of environmental research and public health · 2022Article
- Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature.EClinicalMedicine · 2022Article
- Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data.BMC complementary medicine and therapies · 2022Article
- Health misinformation: protocol for a hybrid concept analysis and development.HRB open research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Twitter, prompted by the rapid spread of alternative narratives, started actively warning users about the spread of COVID-19 misinformation. This form of soft moderation comes in two forms: as an interstitial cover before the Tweet is displayed to the user or as a contextual tag displayed below the Tweet. We conducted a 319-participants study with both verified and misleading Tweets covered or tagged with the COVID-19 misinformation warnings to investigate how Twitter users perceive the accuracy of COVID-19 vaccine content on Twitter. The results suggest that the interstitial covers work, but not the contextual tags, in reducing the perceived accuracy of COVID-19 misinformation. Soft moderation is known to create so-called "belief echoes" where the warnings echo back, instead of dispelling, preexisting beliefs about morally-charged topics. We found that such "belief echoes" do exist among Twitter users in relationship to the perceived safety and efficacy of the COVID-19 vaccine as well as the vaccination hesitancy for themselves and their children. These "belief echoes" manifested as skepticism of adequate COVID-19 immunization particularly among Republicans and Independents as well as female Twitter users. Surprisingly, we found that the belief echoes are strong enough to preclude adult Twitter users to receive the COVID-19 vaccine regardless of their education level.
Indexed as
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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.