ArticleJournal of computational social science2020
Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams.
Article in Journal of computational social science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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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
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025Pooled it
- Measuring the effects of misinformation exposure and beliefs on behavioural intentions: a COVID-19 vaccination study.Cognitive research: principles and implications · 2022Pooled it
- Hooked on virtual social life. Problematic social media use and associations with mental distress and addictive disorders.PloS one · 2021Trial
- Unraveling the Use of Disinformation Hashtags by Social Bots During the COVID-19 Pandemic: Social Networks Analysis.JMIR infodemiology · 2025Article
- The efficacy of Facebook's vaccine misinformation policies and architecture during the COVID-19 pandemic.Science advances · 2023Article
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- Article
- Vaccination trials on hold: malicious and low credibility content on Twitter during the AstraZeneca COVID-19 vaccine development.Computational and mathematical organization theory · 2022Article
- Sentinel node approach to monitoring online COVID-19 misinformation.Scientific reports · 2022Article
- Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics.PloS one · 2022Article
- Content and Dynamics of Websites Shared Over Vaccine-Related Tweets in COVID-19 Conversations: Computational Analysis.Journal of medical Internet research · 2021Article
- Viruses, Vaccines, and COVID-19: Explaining and Improving Risky Decision-making.Journal of applied research in memory and cognition · 2021Article
- CoVerifi: A COVID-19 news verification system.Online social networks and media · 2021Article
- COVID-19 fake news diffusion across Latin America.Social network analysis and mining · 2021Article
- Misinformation, manipulation, and abuse on social media in the era of COVID-19.Journal of computational social science · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article investigates the prevalence of high and low quality URLs shared on Twitter when users discuss COVID-19. We distinguish between high quality health sources, traditional news sources, and low quality misinformation sources. We find that misinformation, in terms of tweets containing URLs from low quality misinformation websites, is shared at a higher rate than tweets containing URLs on high quality health information websites. However, both are a relatively small proportion of the overall conversation. In contrast, news sources are shared at a much higher rate. These findings lead us to analyze the network created by the URLs referenced on the webpages shared by Twitter users. When looking at the combined network formed by all three of the source types, we find that the high quality health information network, the low quality misinformation network, and the news information network are all well connected with a clear community structure. While high and low quality sites do have connections to each other, the connections to and from news sources are more common, highlighting the central brokerage role news sources play in this information ecosystem. Our findings suggest that while low quality URLs are not extensively shared in the COVID-19 Twitter conversation, a well connected community of low quality COVID-19 related information has emerged on the web, and both health and news sources are connecting to this community.
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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.