Can Fighting Misinformation Have a Negative Spillover Effect? How Warnings for the Threat of Misinformation Can Decrease General News Credibility
Open accessAbstract
In the battle against misinformation, do negative spillover effects of communicative efforts intended to protect audiences from inaccurate information exist?Given the relatively limited prevalence of misinformation in people's news diets, this study explores if the heightened salience of misinformation as a persistent societal threat can have an unintended spillover effect by decreasing the credibility of factually accurate news.Using an experimental design (N = 1305), we test whether credibility ratings of factually accurate news are subject to exposure to misinformation, corrective information, misinformation warnings, and news media literacy (NML) interventions relativizing the misinformation threat.Findings suggest that efforts like warning about the threat of misinformation can prime general distrust in authentic news, hinting toward a deception bias in the context of fear of misinformation being salient.Next, the successfulness of NML interventions is not straight forward if it comes to avoiding that the salience of misinformation distorts people's creditability accuracy.We conclude that the threats of the misinformation order may not just be remedied by fighting false information, but also by reestablishing trust in legitimate news.
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Emphasizing the harms of deepfakes may cause declining trust in all information, including true content.
“emphasizing the harms of deepfakes may cause declining trust in all information, including true content (also see Van der Meer et al., 2023).”
From How persuasive are political cheapfakes disseminated via social media? The effects of out-of-context visual disinformation on message credibility and issue agreement (2025) · cites this paper as Van der Meer et al., 2023
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Beyond Skepticism: Framing Media Literacy Tips to Promote Reliable InformationPreprint
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Thinking Hard, Thinking Smart: How News Users’ Cognitive Traits Guide Their Responses to Fact-Checks
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- Authors
- van der Meer, T. G. L. A., Hameleers, M., & Ohme, J.
- Affiliations
- Amsterdam School of Communications Research (ASCoR), University of Amsterdam, Amsterdam, The Netherlands
- University of Amsterdam (NL)
- Weizenbaum Institute (DE)
- Venue
- Journalism Studies
- Publisher
- Informa UK Limited
- Published
- 2023-03-16
- Volume
- 24
- Issue
- 6
- Pages
- 803-823
- ISSN
- 1461-670X (ISSN-L)
- 1469-9699
- OpenAlex
- W4327555979
- Cited by
- 121
- References
- 70
- Citations by year
- 2026: 29 · 2025: 43 · 2024: 35 · 2023: 13 · 2022: 1
- FWCI
- 51.57
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journalism Studies (publishedVersion, cc-by)
- UvA-DARE (University of Amsterdam) (publishedVersion, cc-by-nc)
- Refubium (Universitätsbibliothek der Freien Universität Berlin) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Universitätsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver (cc-by)
- Funders
- Netherlands Organization for Scientific Research
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Communication › Journalism and Media Studies
- Keywords
- misinformation, news credibility, spillover effects, corrective information
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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