ReviewNature2024
Misunderstanding the harms of online misinformation.
Review in Nature, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Untrustworthy sources on Facebook and Instagram in 2020: Concentrated exposure but no attitudinal effects.Science advances · 2026Article
- Impact of Repeated Exposure to Polarized Health-Related News on Explicit and Implicit Attitudes Toward Dietary Supplements: Online Experimental Study.JMIR infodemiology · 2026Article
- Redesigning algorithms to intervene on social norm misperceptions during a national election.Nature · 2026Article
- We Can No Longer Ignore Cassandra's Warnings.EcoHealth · 2026Article
- The era of "Infectious Diseases+" has arrived: multi-disciplinary integration in pediatric infectious disease prevention and control.Frontiers in pediatrics · 2026Review
- Ad-based social media interventions increase belief accuracy and generate pro-social opinions among non-news readers.PloS one · 2026Article
- The evolving study of political polarization.Open research Europe · 2026Review
- The limited effects of social media use on misperceptions Social media's limited role in misperceptions.PloS one · 2026Article
- How social learning enhances-or undermines-efficiency and flexibility in collective decision-making under uncertainty.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Counterfeit judgments in large language models.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Parental policy-related worry and low-income families' well-being in the context of U.S. executive orders: A cross-sectional analysis.Preventive medicine reports · 2025Article
- Article
- The simulation of judgment in LLMs.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Advocating for a community-centred model for responding to potential information harms.Nature human behaviour · 2025Review
- [AI-enabled clinical decision support systems: challenges and opportunities].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025Review
- Relative engagement with sources of climate misinformation is growing across social media platforms.Scientific reports · 2025Article
- A research agenda for encouraging prosocial behaviour on social media.Nature human behaviour · 2025Review
- Neural mechanisms of cognitive conflict: processing COVID-19 vaccine misinformation.Frontiers in neuroscience · 2025Article
- Modeling the amplification of epidemic spread by individuals exposed to misinformation on social media.Npj complexity · 2025Article
- Complex systems perspective in assessing risks in artificial intelligence.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The controversy over online misinformation and social media has opened a gap between public discourse and scientific research. Public intellectuals and journalists frequently make sweeping claims about the effects of exposure to false content online that are inconsistent with much of the current empirical evidence. Here we identify three common misperceptions: that average exposure to problematic content is high, that algorithms are largely responsible for this exposure and that social media is a primary cause of broader social problems such as polarization. In our review of behavioural science research on online misinformation, we document a pattern of low exposure to false and inflammatory content that is concentrated among a narrow fringe with strong motivations to seek out such information. In response, we recommend holding platforms accountable for facilitating exposure to false and extreme content in the tails of the distribution, where consumption is highest and the risk of real-world harm is greatest. We also call for increased platform transparency, including collaborations with outside researchers, to better evaluate the effects of online misinformation and the most effective responses to it. Taking these steps is especially important outside the USA and Western Europe, where research and data are scant and harms may be more severe.
Indexed as
Identifiers
38840013What 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.