Judging Truth
Abstract
Deceptive claims surround us, embedded in fake news, advertisements, political propaganda, and rumors. How do people know what to believe? Truth judgments reflect inferences drawn from three types of information: base rates, feelings, and consistency with information retrieved from memory. First, people exhibit a bias to accept incoming information, because most claims in our environments are true. Second, people interpret feelings, like ease of processing, as evidence of truth. And third, people can (but do not always) consider whether assertions match facts and source information stored in memory. This three-part framework predicts specific illusions (e.g., truthiness, illusory truth), offers ways to correct stubborn misconceptions, and suggests the importance of converging cues in a post-truth world, where falsehoods travel further and faster than the truth.
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Even individuals with excellent critical thinking skills can struggle to assess sources for their expertise.
“Research indicates that even individuals with excellent critical thinking skills can struggle to assess sources for their expertise (Brashier & Marsh, 2020).”
From Learning to evaluate sources of science (mis)information on the internet: Assessing students' scientific online reasoning (2025) · cites this paper as Brashier & Marsh, 2020
Negative emotions can reduce gullibility.
“Recent research in social psychology suggests that negative emotions can reduce gullibility (50, 51)”
From Deepfake detection by human crowds, machines, and machine-informed crowds (2022) · cites this paper as [50]
Cites
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The psychological drivers of misinformation belief and its resistance to correction
Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K., & Amazeen, M. A. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-021-00006-y · Cited by 1,372 · see citing works
Self-citationReliance on emotion promotes belief in fake news
Martel, C., Pennycook, G., & Rand, D. G. (2020) · Cognitive Research: Principles and Implications · doi:10.1186/s41235-020-00252-3 · Cited by 470 · see citing works
Deepfake detection by human crowds, machines, and machine-informed crowds
Groh, M., Epstein, Z., Firestone, C., & Picard, R. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2110013119 · Cited by 248 · see citing works
Factuality challenges in the era of large language models and opportunities for fact-checking
Augenstein, I., Baldwin, T., Cha, M., Chakraborty, T., Ciampaglia, G. L., Corney, D., DiResta, R., Ferrara, E., Hale, S., Halevy, A., et al. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00881-z · Cited by 187 · see citing works
Reliance on emotion promotes belief in fake news
Martel, C., Pennycook, G., & Rand, D. G. (2019) · doi:10.31234/osf.io/a2ydw · Cited by 49 · see citing works
Media, technology, and the sins of memory
Schacter, D. L. (2022) · Memory, Mind & Media · doi:10.1017/mem.2021.3 · Cited by 40 · see citing works
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Digitising “The Big Lie”: Algorithmic Curation as an Inhibitor of Media Exposure Diversity Online
Reid, J. (2024) · Communicatio · doi:10.1080/02500167.2024.2424841 · Cited by 10 · see citing works
- Authors
- Brashier, N. M., & Marsh, E. J.
- Affiliations
- Harvard University (US)
- Duke University (US)
- Venue
- Annual Review of Psychology
- Publisher
- Annual Reviews
- Published
- 2020-01-04
- Volume
- 71
- Issue
- 1
- Pages
- 499-515
- ISSN
- 0066-4308 (ISSN-L)
- 1545-2085
- OpenAlex
- W4230186188
- Cited by
- 288
- References
- 15
- Citations by year
- 2026: 40 · 2025: 46 · 2024: 48 · 2023: 61 · 2022: 38 · 2021: 28 · 2020: 24 · 2019: 3
- FWCI
- 5.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Psychology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- truth judgments, belief formation, deception, fake news, truthiness, illusory truth effect, memory consistency, post-truth, misinformation, political propaganda, rumors, misconceptions
- MeSH terms
- Humans, Judgment, Deception
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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.
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