Prior exposure increases perceived accuracy of fake news
Open accessAbstract
The 2016 U.S. presidential election brought considerable attention to the phenomenon of "fake news": entirely fabricated and often partisan content that is presented as factual. Here we demonstrate one mechanism that contributes to the believability of fake news: fluency via prior exposure. Using actual fake-news headlines presented as they were seen on Facebook, we show that even a single exposure increases subsequent perceptions of accuracy, both within the same session and after a week. Moreover, this "illusory truth effect" for fake-news headlines occurs despite a low level of overall believability and even when the stories are labeled as contested by fact checkers or are inconsistent with the reader's political ideology. These results suggest that social media platforms help to incubate belief in blatantly false news stories and that tagging such stories as disputed is not an effective solution to this problem. It is interesting, however, that we also found that prior exposure does not impact entirely implausible statements (e.g., "The earth is a perfect square"). These observations indicate that although extreme implausibility is a boundary condition of the illusory truth effect, only a small degree of potential plausibility is sufficient for repetition to increase perceived accuracy. As a consequence, the scope and impact of repetition on beliefs is greater than has been previously assumed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Simply being exposed to misinformation can increase subsequent belief.
“Reducing the sharing of misinformation is of substantial importance, because simply being exposed to misinformation can increase subsequent belief13,20–22.”
From Accuracy prompts are a replicable and generalizable approach for reducing the spread of misinformation (2022) · cites this paper as [13]
Some explanations for belief in misinformation identify factors that resist intervention, while others propose policy approaches that are effective in practice but difficult to scale.
“Some explanations for belief in misinformation identify factors that resist intervention (4), while others propose policy approaches that are effective in practice but difficult to scale (34, 44).”
From A digital media literacy intervention increases discernment between mainstream and false news in the United States and India (2020) · cites this paper as [44]
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Timing matters when correcting fake news
Brashier, N. M., Pennycook, G., Berinsky, A. J., & Rand, D. G. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2020043118 · Cited by 216 · see citing works
“Ideally, people would not see misinformation in the first place, since even a single exposure to a fake headline makes it seem truer (20).”
BackgroundSelf-citationBryanov, K., & Vziatysheva, V. (2021) · PLOS ONE · doi:10.1371/journal.pone.0253717 · Cited by 211 · see citing works
“[47] provide evidence supporting the existence of the illusory truth effect—the increased likelihood to view the already seen statements as true, regardless of the actual veracity—in the context of fake news.”
BackgroundPolitical Psychology in the Digital (mis)Information age: A Model of News Belief and Sharing
Van Bavel, J. J., Harris, E. A., Pärnamets, P., Rathje, S., Doell, K. C., & Tucker, J. A. (2021) · Social Issues and Policy Review · doi:10.1111/sipr.12077 · Cited by 213 · see citing works
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284 · see citing works
“There is some evidence from survey experiments that misinformation seen online is believed (Pereira and Van Bavel 2018), particularly by partisans (however, partisans may be able to identify even agreeable headlines as fake when “blatantly inaccurate” [Pennycook and Rand 2018]), those less prone to analytic reasoning…”
BackgroundRepetition increases perceived truth equally for plausible and implausible statements
Fazio, L. K., Rand, D. G., & Pennycook, G. (2019) · Psychonomic Bulletin & Review · doi:10.3758/s13423-019-01651-4 · Cited by 205 · see citing works
Scaling up fact-checking using the wisdom of crowds
Allen, J., Arechar, A. A., Pennycook, G., & Rand, D. G. (2021) · Science Advances · doi:10.1126/sciadv.abf4393 · Cited by 234 · see citing works
Self-citationTruth by Repetition: Explanations and Implications
Unkelbach, C., Koch, A. S., Silva, R. R., & Garcia‐Marques, T. (2019) · Current Directions in Psychological Science · doi:10.1177/0963721419827854 · Cited by 183 · see citing works
A Signal Detection Approach to Understanding the Identification of Fake News
Batailler, C., Brannon, S. M., Teas, P. E., & Gawronski, B. (2021) · Perspectives on Psychological Science · doi:10.1177/1745691620986135 · Cited by 185 · see citing works
“To investigate the emergence of illusory truth effects in the context of fake news, Pennycook et al. (2018) used a paradigm in which participants first indicated for a set of real and fake news headlines whether they would share the story.”
BackgroundMethodResultInfluentialPausing to consider why a headline is true or false can help reduce the sharing of false news
Fazio, L. (2020) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-009 · Cited by 187 · see citing works
Spread of misinformation on social media: What contributes to it and how to combat it
Chen, S., Xiao, L., & Kumar, A. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107643 · Cited by 211 · see citing works
Lower Artificial Intelligence Literacy Predicts Greater AI Receptivity
Tully, S. M., Longoni, C., & Appel, G. (2025) · Journal of Marketing · doi:10.1177/00222429251314491 · Cited by 186 · see citing works
Understanding Fake News Consumption: A Review
Baptista, J. P., & Gradim, A. (2020) · Social Sciences · doi:10.3390/socsci9100185 · Cited by 202 · see citing works
“Even though this exposure is later denied by fact-checkers, the user can continue to believe in its content (Pennycook et al. 2018).”
BackgroundMistrust and misinformation: A two-component, socio-epistemic model of belief in conspiracy theories
Pierre, J. M. (2020) · Journal of Social and Political Psychology · doi:10.5964/jspp.v8i2.1362 · Cited by 182 · see citing works
Sinatra, G. M., & Lombardi, D. (2020) · Educational Psychologist · doi:10.1080/00461520.2020.1730181 · Cited by 183 · see citing works
Mosleh, M., Pennycook, G., & Rand, D. G. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228882 · Cited by 172 · see citing works
“This seems unlikely, however, for two reasons: popularity on social media tends to be extremely ephemeral, and experimental evidence suggests that being familiar with a story actually makes people less likely to say they would share it, rather than more likely [13].”
BackgroundMethodResultInfluentialkeersmaecker, J. D., Dunning, D. A., Pennycook, G., Rand, D. G., Sanchez, C. J., Unkelbach, C., & Roets, A. (2019) · Personality and Social Psychology Bulletin · doi:10.1177/0146167219853844 · Cited by 165 · see citing works
“The illusory truth effect, referring to people’s tendency to believe repeated information more compared with new information, can have a profound impact on individuals (Brown & Nix, 1996) and society at large (Pennycook et al., 2018).”
BackgroundMethodResultInfluentialUnderstanding and combatting misinformation across 16 countries on six continents
Arechar, A. A., Allen, J., Berinsky, A. J., Cole, R., Epstein, Z., Garimella, K., Gully, A., Lu, J. G., Ross, R. M., Stagnaro, M. N., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01641-6 · Cited by 188 · see citing works
Educative Interventions to Combat Misinformation: Evidence from a Field Experiment in India
Badrinathan, S. (2021) · American Political Science Review · doi:10.1017/s0003055421000459 · Cited by 160 · see citing works
Effron, D. A., & Raj, M. (2019) · Psychological Science · doi:10.1177/0956797619887896 · Cited by 160 · see citing works
Big Data and quality data for fake news and misinformation detection
Asr, F. T., & Taboada, M. (2019) · Big Data & Society · doi:10.1177/2053951719843310 · Cited by 157 · see citing works
“Fact checking could even be counterproductive, as fact-checking a story or a rumour leads to familiarity with it, and familiarity breeds not contempt but acceptance (Berinsky, 2017; Ecker et al., 2017; Pennycook et al., 2018; Swire et al., 2017).”
BackgroundMisunderstanding the harms of online misinformation
Budak, C., Nyhan, B., Rothschild, D. M., Thorson, E., & Watts, D. J. (2024) · Nature · doi:10.1038/s41586-024-07417-w · Cited by 156 · see citing works
The Effectiveness of Social Norms in Fighting Fake News on Social Media
Gimpel, H., Heger, S., Olenberger, C., & Utz, L. (2021) · Journal of Management Information Systems · doi:10.1080/07421222.2021.1870389 · Cited by 156 · see citing works
“The more people hear a story, the more familiar it becomes, and the more likely they are to believe it as real [37, 67, 77].”
BackgroundQuantifying the effects of fake news on behavior: Evidence from a study of COVID-19 misinformation.
Greene, C. M., & Murphy, G. (2021) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000371 · Cited by 151 · see citing works
An initial accuracy focus prevents illusory truth
Brashier, N. M., Eliseev, E. D., & Marsh, E. J. (2019) · Cognition · doi:10.1016/j.cognition.2019.104054 · Cited by 146 · see citing works
“As examples, they choose to share news they recognize as false (Pennycook et al., 2018; Pew Research Center, 2016), tell frequent lies (Serota, Levine, & Boster, 2010), and fall for fake headlines because of “lazy thinking” (Pennycook & Rand, 2019).”
BackgroundPersonal experiences bridge moral and political divides better than facts
Kubin, E., Puryear, C., Schein, C., & Gray, K. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2008389118 · Cited by 209 · see citing works
“Most recently, claims of “fake news” allow people to distrust any information that fails to align with their political beliefs (24, 25) and to trust fake news that aligns with their beliefs (26).”
BackgroundTangherlini, T. R., Shahsavari, S., Shahbazi, B., Ebrahimzadeh, E., & Roychowdhury, V. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233879 · Cited by 146 · see citing works
“Conspiracy theories and their factual counterpart, conspiracies, have long been studied by scholars from a broad range of disciplines, including political science [1][2][3][4], philosophy [5], psychology [6][7][8][9][10][11][12][13][14][15], law [16], sociology [17][18], linguistics and language use [19][20], folklore…”
BackgroundBoberg, S., Quandt, T., Schatto-Eckrodt, T., & Frischlich, L. (2020) · arXiv · doi:10.48550/arxiv.2004.02566 · Cited by 141 · see citing works
“It is noteworthy that this information mix is much more likely to contribute to the feared “infodemic” (WHO, 2020a) as media users are usually better in noting highly non-credible sources and disinformation bits (Pennycook et al., 2018; Pennycook and Rand, 2019).”
BackgroundPereira, A., Harris, E., & Bavel, J. J. V. (2021) · Group Processes & Intergroup Relations · doi:10.1177/13684302211030004 · Cited by 140 · see citing works
“This is a problem because familiarity with (fake) news increases perceptions of accuracy (Pennycook et al., 2018).”
BackgroundBDANN: BERT-Based Domain Adaptation Neural Network for Multi-Modal Fake News Detection
Zhang, T., Wang, D., Chen, H., Zeng, Z., Guo, W., Miao, C., & Cui, L. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9206973 · Cited by 140 · see citing works
“According to [3], people are more likely to believe fake news even if they do not align with the viewer’s political inclination.”
BackgroundJones-Jang, S. M., Geng, T., Li, J.-Y., Xia, R., Huang, C., Kim, H., & Tang, J. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.02.032 · Cited by 134 · see citing works
False Memories for Fake News During Ireland’s Abortion Referendum
Murphy, G., Loftus, E. F., Grady, R. H., Levine, L. J., & Greene, C. M. (2019) · Psychological Science · doi:10.1177/0956797619864887 · Cited by 134 · see citing works
“Research has demonstrated that explicit warnings about the possibility of misinformation can sometimes modestly reduce false memories and beliefs (e.g., Blank & Launay, 2014; Pennycook, Cannon, & Rand, 2018; Qin, Ogle, & Goodman, 2008).”
Modirrousta-Galian, A., & Higham, P. A. (2023) · Journal of Experimental Psychology General · doi:10.1037/xge0001395 · Cited by 144 · see citing works
Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views
Prieto-Curiel, R., & Ramírez, H. G. (2021) · Scientific Reports · doi:10.1038/s41598-021-85555-1 · Cited by 128 · see citing works
News from Generative Artificial Intelligence Is Believed Less
Longoni, C., Fradkin, A., Cian, L., & Pennycook, G. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533077 · Cited by 128 · see citing works
Beyond “fake news”: Analytic thinking and the detection of false and hyperpartisan news headlines
Ross, R. M., Rand, D. G., & Pennycook, G. (2021) · Judgment and Decision Making · doi:10.1017/s1930297500008640 · Cited by 126 · see citing works
“This may be problematic, because even a single prior exposure to a false political headline can increase later belief in the headline (Pennycook, Cannon & Rand, 2018).”
How persuasive is AI-generated propaganda?
Goldstein, J. A., Chao, J., Grossman, S., Stamos, A., & Tomz, M. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae034 · Cited by 133 · see citing works
“SEs and 95% CIs are shown. exposed multiple times (18), that repeated exposure to content on a social media platform leads to a higher rate of sharing that content (19, 20), and that belief in false information continues to grow loga-rithmically with additional exposures (21).”
BackgroundFacts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation
Keller, D., & Leerssen, P. (2020) · Data Archiving and Networked Services (DANS) · doi:10.1017/9781108890960
Fake news agenda in the era of COVID-19: Identifying trends through fact-checking content
Ceron, W., de‐Lima‐Santos, M., & Quiles, M. G. (2020) · Online Social Networks and Media · doi:10.1016/j.osnem.2020.100116 · Cited by 122 · see citing works
“A closer look at the literature on fact-checking and fake news argues that the repetition of debunks makes it more believable by the public, however, reveals a number of gaps and shortcomings[80, 6].”
Backgroundvan der Meer, T. G. L. A., Hameleers, M., & Ohme, J. (2023) · Journalism Studies · doi:10.1080/1461670x.2023.2187652 · Cited by 121 · see citing works
“Since being able to form accurate beliefs based on credible information is at the heart of a well-functioning democracy (Pennycook, Cannon, and Rand 2018), the present study is set out to assess if the public debate about misinformation and communicative attempts to correct it (such as…”
BackgroundMartel, C., & Rand, D. G. (2023) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2023.101710 · Cited by 122 · see citing works
Deepfake news: AI-enabled disinformation as a multi-level public policy challenge
Whyte, C. (2020) · Journal of Cyber Policy · doi:10.1080/23738871.2020.1797135 · Cited by 119 · see citing works
Siegel, A. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.005 · Cited by 117 · see citing works
Carey, J. M., Guess, A. M., Loewen, P. J., Merkley, E., Nyhan, B., Phillips, J. B., & Reifler, J. (2022) · Nature Human Behaviour · doi:10.1038/s41562-021-01278-3 · Cited by 118 · see citing works
Jahanbakhsh, F., Zhang, A. X., Berinsky, A. J., Pennycook, G., Rand, D. G., & Karger, D. R. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449092 · Cited by 112 · see citing works
“This phenomenon has also been reported in [51], where Pennycook et al. found that even a single prior exposure to a headline increases subsequent perceptions of its accuracy.”
BackgroundEcker, U. K. H., Lewandowsky, S., & Chadwick, M. (2020) · Cognitive Research Principles and Implications · doi:10.1186/s41235-020-00241-6 · Cited by 117 · see citing works
Chadwick, A., & Stanyer, J. (2021) · Communication Theory · doi:10.1093/ct/qtab019 · Cited by 129 · see citing works
Accuracy and social motivations shape judgements of (mis)information
Rathje, S., Roozenbeek, J., Bavel, J. J. V., & van der Linden, S. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01540-w · Cited by 134 · see citing works
“Numerous studies suggest that misinformation exposure 1 may reduce support for climate change 5,6 and the COVID-19 vaccine 7,8 , and that the mere repetition of misinformation can increase belief in it 9,10 .”
Fernández, M., & Alani, H. (2018) · International World Wide Web Conference (WWW) · doi:10.1145/3184558.3188730 · Cited by 111 · see citing works
Bishop, D. (2019) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021819886519 · Cited by 109 · see citing works
The emerging science of content labeling: Contextualizing social media content moderation
Morrow, G., Swire-Thompson, B., Polny, J., Kopec, M., & Wihbey, J. (2020) · J. Assoc. Inf. Sci. Technol. · doi:10.1002/asi.24637 · Cited by 120 · see citing works
“However, plausibility does serve as a boundary condition for illusory truth where statements with extremely low believability, such as “ the Earth is a perfect square, ” did not increase perceptions of accuracy when repeated (Pennycook et al., 2018).”
BackgroundMosleh, M., Martel, C., Eckles, D., & Rand, D. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445642 · Cited by 106 · see citing works
“warning [8-10], although tagging some false content may increase the sharing of untagged false content via the “implied truth efect””
BackgroundSelf-citationTraberg, C. S., & van der Linden, S. (2021) · Personality and Individual Differences · doi:10.1016/j.paid.2021.111269 · Cited by 104 · see citing works
Roozenbeek, J., Maertens, R., Herzog, S. M., Geers, M., Kurvers, R. H. J. M., Sultan, M., & van der Linden, S. (2022) · Judgment and Decision Making · doi:10.1017/s1930297500003570 · Cited by 94 · see citing works
Russian propaganda on social media during the 2022 invasion of Ukraine
Geissler, D., Bär, D., Pröllochs, N., & Feuerriegel, S. (2023) · EPJ Data Science · doi:10.1140/epjds/s13688-023-00414-5 · Cited by 136 · see citing works
“This is especially alarming, since repeated exposure can lead people to perceive misinformation as accurate [67].”
BackgroundCredible Threat: Attacks Against Women Online and the Future of Democracy
Sobieraj, S. (2020) · doi:10.1093/oso/9780190089283.001.0001 · Cited by 100 · see citing works
Higher-order interactions shape collective human behaviour
Battiston, F., Capraro, V., Karimi, F., Lehmann, S., Migliano, A. B., Sadekar, O., Sánchez, Á., & Perc, M. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02373-5 · Cited by 99 · see citing works
“Self-serving lies are associated with adverse personal outcomes, such as marital dissatisfaction 168 and friendship dissolution 169 , considerable economic losses due to tax evasion 170 and insurance fraud 171 , and threats to democratic processes due to the spread of misinformation 172 .”
Performance on the Cognitive Reflection Test is stable across time
Stagnaro, M. N., Pennycook, G., & Rand, D. G. (2018) · Judgment and Decision Making · doi:10.1017/s1930297500007695 · Cited by 100 · see citing works
Cognitive Reflection and the 2016 U.S. Presidential Election
Pennycook, G., & Rand, D. G. (2018) · Personality and Social Psychology Bulletin · doi:10.1177/0146167218783192 · Cited by 99 · see citing works
Altay, S., de Araujo, E., & Mercier, H. (2021) · Digital Journalism · doi:10.1080/21670811.2021.1941163 · Cited by 97 · see citing works
“…(Experiment 2) A growing body of research suggests that people may come to believe in fake news because they have been repeatedly exposed to them (Pennycook, Cannon, and Rand 2018; Pennycook and Rand 2020), an effect of repetition on truth judgments known as ‘illusory truth,’ which had been…”
BackgroundMethodInfluentialNadarevic, L., Reber, R., Helmecke, A. J., & Köse, D. (2020) · Cognitive Research Principles and Implications · doi:10.1186/s41235-020-00251-4 · Cited by 99 · see citing works
Human Cooperation and the Crises of Climate Change, COVID-19, and Misinformation.
van Lange, P., & Rand, D. (2021) · Annual Review of Psychology · doi:10.1146/annurev-psych-020821-110044 · Cited by 94 · see citing works
- Authors
- Pennycook, G., Cannon, T. D., & Rand, D. G.
- Affiliations
- Yale University (US)
- Venue
- Journal of Experimental Psychology General
- Published
- 2018-12
- Volume
- 147
- Issue
- 12
- Pages
- 1865-1880
- ISSN
- 0096-3445 (ISSN-L)
- 1939-2222
- PMC
- PMC6279465
- OpenAlex
- W3125618971
- Cited by
- 1,268
- References
- 58
- Citations by year
- 2026: 117 · 2025: 139 · 2024: 141 · 2023: 204 · 2022: 188 · 2021: 198 · 2020: 180 · 2019: 79 · 2018: 20 · 2017: 2
- FWCI
- 270.78
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Experimental Psychology General (publishedVersion, other-oa)
- SSRN Electronic Journal (acceptedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- Social Sciences and Humanities Research Council of Canada
- National Institute of Mental Health (MH081902)
- Templeton World Charity Foundation
- Defense Advanced Research Projects Agency
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Keywords
- fake news, illusory truth effect, prior exposure, perceived accuracy, fluency, social media, Facebook, 2016 US presidential election, fact-checking, political ideology, belief formation, repetition
- MeSH terms
- Adult, Female, Humans, Judgment, Deception, Male, Perception, Politics, United States, Social Media
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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