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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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“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]
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“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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BackgroundMistakes, Overconfidence, and the Effect of Sharing on Detecting Lies
Serra-García, M., & Uri Gneezy, B. (2021) · American Economic Review · doi:10.1257/aer.20191295 · Cited by 54
The evolution of lying in well-mixed populations
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Liv, N., & Greenbaum, D. S. (2020) · AJOB Neuroscience · doi:10.1080/21507740.2020.1740351 · Cited by 54
“…and biases inherent in our System 1 thinking, research has shown that prior exposure to fake news and false information increases the subsequent believability of that news, regardless of the independent, unbiased and objective level of believability of that information (Pennycook et al. 2018).”
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Fake news self-efficacy, fake news identification, and content sharing on Facebook
Hopp, T. (2021) · Journal of Information Technology & Politics · doi:10.1080/19331681.2021.1962778 · Cited by 53
“Pennycook, Cannon, and Rand (2018), for example, found evidence that belief in false political information stems partly from the illusory truth effect , or the idea that prior exposure to a statement of purported fact increases the probability that the statement will be judged as a factually…”
BackgroundAghajari, Z., Baumer, E. P. S., & DiFranzo, D. J. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579520 · Cited by 57
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“For instance, even though students use Google to check the validity of the news, they may end up with multiple web pages rereading the same article, which in turn, increases its believability as a legitimate article (Fielden et al., 2018; Pennycook et al., 2018).”
BackgroundRegulating Recommending: Motivations, Considerations, and PrinciplesPreprint
Cobbe, J., & Singh, J. P. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3371830 · Cited by 47
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BackgroundThe effects of repetition on belief in naturalistic settings.
Fazio, L. K., Pillai, R. M., & Patel, D. (2022) · Journal of Experimental Psychology General · doi:10.1037/xge0001211 · Cited by 53
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What do we study when we study misinformation? A scoping review of experimental research (2016-2022)
Murphy, G., Laurent, C. D. S., Reynolds, M., Aftab, O., Hegarty, K., Sun, Y., & Greene, C. M. (2023) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-130 · Cited by 63
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The Influence of Political Ideology on Fake News Belief: The Portuguese Case
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“Research has shown that users do not rely purely on informational veracity when assessing the validity of a news article (Pennycook et al., 2018).”
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“Although there is extensive research [56,57] highlighting a general distrust and negative attitude toward for-profit content [58], our results revealed a significant interaction between information type and content category.”
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“These effects are further compounded by an “illusory truth effect” wherein individuals have greater confidence in the truthfulness of a claim given past exposure— a dynamic observed even in evaluations of fake news (Pennycook et al., 2018).”
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Does Analytic Thinking Insulate Against Pro‐Kremlin Disinformation? Evidence From Ukraine
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“The perceived truthfulness of misinformation can be manipulated experimentally; studies have shown that multiple exposures to a given fake news headline can increase its perceived accuracy (De keersmaecker et al., 2020; Fazio, 2020; Newman et al., 2020; Pennycook et al., 2018).”
BackgroundPublic Health Communication and Engagement on Social Media during the COVID-19 PandemicPreprint
Teichmann, L., Nossek, S., Bridgman, A., Loewen, P. J., Owen, T., Ruths, D. A., & Zhilin, O. (2020) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/7hypj · Cited by 43
Labeling AI-generated media online
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Believing and Sharing Information by Fake Sources: An Experiment
Bauer, P. C., & von Hohenberg, B. C. (2020) · Political Communication · doi:10.1080/10584609.2020.1840462 · Cited by 52
“It is, however, much smaller than individual-level predictors of belief such as familiarity with a story in Pennycook et al. (2018).”
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Epstein, Z. G., Fang, M. C., Arechar, A. A., & Rand, D. G. (2023) · doi:10.31234/osf.io/v4mfz · Cited by 41
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“In such cases, individuals are not assessing the plausibility of the information presented to them, but rather trusting the information simply because it is familiar (Lewandowsky et al., 2012; Pennycook et al., 2018).”
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Domgaard, S., & Park, M. (2021) · Health Education Journal · doi:10.1177/00178969211038750 · Cited by 46
From Low-Choice to High-Choice Media Environments
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Misinformation detection on online social networks using pretrained language models
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Bots and Computational Propaganda: Automation for Communication and Control
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BackgroundFacts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation
Keller, D., & Leerssen, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.011 · Cited by 39
Deepfakes on Twitter: Which Actors Control Their Spread?
Pérez Dasilva, J., Meso Ayerdi, K., & Mendiguren Galdospin, T. (2021) · Media and Communication · doi:10.17645/mac.v9i1.3433 · Cited by 38
“Although deepfakes have become a topic of debate, academic research has only just recently begun addressing digital disinformation on social media (Anderson, 2018), which can be dangerous to the public sphere given the potential to create states of false opinion (Pennycook, Cannon, & Rand, 2018).”
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Ganapini, M. B. (2021) · Mind & Language · doi:10.1111/mila.12373 · Cited by 37
Poligraph: Intrusion-Tolerant and Distributed Fake News Detection System
Shan, G., Zhao, B., Clavin, J. R., Zhang, H., & Duan, S. (2021) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2021.3131026 · Cited by 40
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BotCamp: Bot-driven Interactions in Social Campaigns
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“Not surprisingly, humans tend to believe repeatedly encountered information from diverse sources [22].”
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Ling, C., Gummadi, K. P., & Zannettou, S. (2023) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v17i1.22168 · Cited by 37
“…are believed to be credible), the “backfire effect” [19] (i.e., people strengthen their support for misinformation after seeing interventions), and the “illusory truth effect” [23] (people believe misinformation when exposed to it multiple times, despite the existence of interventions).”
BackgroundHow do we remember public events? Pioneering a new area of everyday memory research
Abel, M., & Berntsen, D. (2021) · Cognition · doi:10.1016/j.cognition.2021.104745 · Cited by 41
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“Encountering a falsehood, or even just knowing about its existence increases its perceived accuracy (Pennycook et al., 2018), therefore also affecting individuals with high epistemic needs for accuracy – those that are most likely to update in line with newly learned information.”
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“Moreover, the nature of social media algorithms may have resulted in repeated exposure to misinformation, which can increase trust in false beliefs through the illusory truth effect, which maintains that repeated information is seen as more truthful 27,28 .”
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“This is Fake! Shared it by Mistake”:Assessing the Intent of Fake News Spreaders
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“Intent to share : Building on prior work that measures sharing intention (e.g., Ha & Ahn, 2011; Moravec et al., 2020; Pennycook et al., 2018; Petit et al., 2021; Stefanone et al., 2019), this index was operationalized using three five-point scale statements including: “ I would recommend this news…”
BackgroundMethodHealth misinformation: what it is, why people believe it, how to counter it
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“Studies also show that repetition signi fi cantly increases perceived accuracy of both plausible and implausible information (Fazio et al., 2019; Pennycook et al., 2018) and that prior knowledge (Fazio et al., 2015) and a disposition toward analytical thinking do not protect one from the illusory…”
BackgroundExamining the Impact of Provenance-Enabled Media on Trust and Accuracy Perceptions
Feng, K. J. K., Ritchie, N., Blumenthal, P., Parsons, A., & Zhang, A. X. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3610061 · Cited by 52
“We measure the correction of one’s perceived accuracy of a claim, or simply Correction , as how much closer one’s perception of accuracy for a claim moves towards the ground truth of that claim after an intervention [12, 88].”
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“Additionally, repeated exposure to misinformation has been shown to increase belief in that misinformation [72].”
Fake news and the willingness to share: a schemer schema and confirmatory bias perspective
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“These warnings could create an implied truth effect [87], generally undermine trust in online content [83]), cause concern about the warning provider, or lead to warning fatigue [20].”
BackgroundInfluentialA Model of Online Misinformation
Acemoğlu, D., Ozdaglar, A., & Siderius, J. (2021) · National Bureau of Economic Research · doi:10.3386/w28884 · Cited by 43
Fool me twice: how effective is debriefing in false memory studies?
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Protection from ‘Fake News’: The Need for Descriptive Factual Labeling for Online Content
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“Additionally, reader laziness [8] and repetition of exposure [9] have been shown to increase consumer belief in deceptive content.”
Background8 Participatory Propaganda: The Engagement of Audiences in the Spread of Persuasive Communications
Wanless, A., & Berk, M. (2022) · doi:10.2478/9788366675612-009 · Cited by 35
When Does an Individual Accept Misinformation? An Extended Investigation Through Cognitive Modeling
Borukhson, D., Lorenz-Spreen, P., & Ragni, M. (2022) · Computational Brain & Behavior · doi:10.1007/s42113-022-00136-3 · Cited by 38
“This is consistent with the finding that repeated exposure to a news item increases its perceived accuracy (Pennycook et al., 2018).”
ResultThe moral psychology of misinformation: Why we excuse dishonesty in a post-truth world
Effron, D. A., & Helgason, B. A. (2022) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2022.101375 · Cited by 41
“Whereas prior work suggests that repetition can increase belief in misinformation [36,37], these studies reveal that repetition can reduce how much people condemn misinformation they know to be false.”
BackgroundDemocratic Creative Destruction? The Effect of a Changing Media Landscape on Democracy
Nielsen, R. K., & Fletcher, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.008 · Cited by 35
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Journalism Students and Information Consumption in the Era of Fake News
Tejedor, S., Oliva, M. P., Bugs, R. C., & Cervi, L. (2021) · Media and Communication · doi:10.17645/mac.v9i1.3516 · Cited by 42
“A recent research by Pennycook, Cannon, and Rand (2018), for example, warns of an ‘illusory truth effect’ linked to fake news headlines.”
BackgroundGwebu, K. L., Wang, J., & Zifla, E. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.2002932 · Cited by 37
“The possibility of confirmation bias serving as a boundary condition for the effects of warnings remains inconclusive (Moravec, Minas, and Dennis 2019; Pennycook, Cannon, and Rand 2018).”
BackgroundResultInfluentialIS FAKE NEWS SPREADING MORE RAPIDLY THAN COVID-19 IN INDIA?
(2020) · Journal of Content Community and Communication · doi:10.31620/jccc.06.20/15 · Cited by 32
The moral repetition effect: Bad deeds seem less unethical when repeatedly encountered.
Effron, D. A. (2022) · Journal of Experimental Psychology General · doi:10.1037/xge0001214 · Cited by 44
Affective information processing of fake news: evidence from NeuroIS
Lutz, B., Adam, M. T. P., Feuerriegel, S., Pröllochs, N., & Neumann, D. (2023) · European Journal of Information Systems · doi:10.1080/0960085x.2023.2224973 · Cited by 38
“However, research has also found that careful thinking is not sufficient to stop users from falling for fake news (e.g., Moravec et al., 2019; Pennycook et al., 2018; Ross et al., 2018), implying that users can inadvertently fall for fake news despite careful thinking.”
InfluentialHwang, Y., & Jeong, S. (2022) · Communication Research · doi:10.1177/00936502221121509 · Cited by 35
“Previous research has shown that repeated exposure to misinformation can increase the perceived accuracy of fake news (Pennycook et al., 2018).”
BackgroundComparing the Willingness to Share for Human-generated vs. AI-generated Fake News
Bashardoust, A., Feuerriegel, S., & Shrestha, Y. R. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3687028 · Cited by 56
Karduni, A., Cho, I., Wesslen, R. S., Santhanam, S., Volkova, S., Arendt, D., Shaikh, S., & Dou, W. (2019) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3301275.3302320 · Cited by 34
“Researchers and practitioners from multiple disciplines including political science, psychology and computer science are grappling with the effects of misinformation and devising means to combat it [13, 39, 47, 48, 59].”
Al-Hasan, A., Khuntia, J., & Yim, D. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.715931 · Cited by 31
“Repeated visibility of misinformation through media outlets daily causes repeated exposure known to increase fake news beliefs (13, 72).”
BackgroundCavelty, M. D., & Wenger, A. (2022) · Routledge eBooks · doi:10.4324/9781003110224 · Cited by 35
Health-related fake news during the COVID-19 pandemic: perceived trust and information search
Zheng, L., Elhai, J. D., Miao, M., Wang, Y., Wang, Y., & Gan, Y. (2022) · Internet Research · doi:10.1108/intr-11-2020-0624 · Cited by 33
Bibliometric analysis of fake news indexed in Web of Science and Scopus (2001-2020)
Patra, R. K., Pandey, N., & Sudarsan, D. (2022) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-11-2021-0177 · Cited by 36
What Makes News Sharable on Social Media?
Chen, X., Pennycook, G., & Rand, D. G. (2023) · Journal of Quantitative Description Digital Media · doi:10.51685/jqd.2023.007 · Cited by 38
Ismail, N., Ismail, D. K. B., Farrell, T., & Kane, A. (2022) · JMIR Formative Research · doi:10.2196/38794 · Cited by 33
“Certain personal characteristics or demographic features have been implicated in the spread of misinformation, for example, the characteristics of extroversion and cooperativeness [10,11], dogmatism and religious beliefs [12], and overconfidence in one’s knowledge and critical analytic skills [13].”
BackgroundLee, T., Johnson, T. J., Jia, C., & Lacasa-Mas, I. (2023) · New Media & Society · doi:10.1177/14614448231202480 · Cited by 31
“Research also suggests that even a single exposure fosters familiarity and increases the perceived accuracy of false information (Pennycook et al., 2018).”
The role of pseudo-cognitive authorities and self-deception in the dissemination of fake news
Froehlich, T. J. (2019) · Open Information Science · doi:10.1515/opis-2019-0009 · Cited by 30
Measuring the scope of pro-Kremlin disinformation on Twitter
Golovchenko, Y. (2020) · Humanities and Social Sciences Communications · doi:10.1057/s41599-020-00659-9 · Cited by 30
Arena, A., Esposti, E. D., Orsini, B., Verrelli, L., Rodondi, G., Lenzi, J., Casadio, P., & Seracchioli, R. (2022) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/j.ejogrb.2022.05.020 · Cited by 30
News Media Credibility Ratings and Perceptions of Online Fake News Exposure in Five Countries
Martin, J. D., & Hassan, F. (2020) · Journalism Studies · doi:10.1080/1461670x.2020.1827970 · Cited by 30
Martel, C., & Rand, D. G. (2023) · doi:10.31234/osf.io/48p2a · Cited by 30
Xue, X., Ma, H., Zhao, Y. C., Zhu, Q., & Song, S. (2024) · Social Science & Medicine · doi:10.1016/j.socscimed.2024.117136 · Cited by 31
The Rhetoric Side of Fake News: A New Weapon for Anti-Politics?
Scardigno, R., & Mininni, G. (2019) · World Futures · doi:10.1080/02604027.2019.1703158 · Cited by 36
Poisoning the information well?
Tandoc, E. C., Duffy, A. M., Jones-Jang, S. M., & Pin, W. G. W. (2021) · Journal of Language and Politics · doi:10.1075/jlp.21029.tan · Cited by 31
Regulating Deep Fakes in the Artificial Intelligence Act
Łabuz, M. (2023) · Applied Cybersecurity & Internet Governance · doi:10.60097/acig/162856 · Cited by 43
Guo, C., Zheng, N., & Guo, C. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3610085 · Cited by 29
“For example, Pennycook et al. [48] suggested that a single exposure to fake news increases subsequent perceptions of accuracy.”
BackgroundMeyer, S., & Elsweiler, D. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103514 · Cited by 39
The Psychological Appeal of Fake-News Attributions
Axt, J. R., Landau, M. J., & Kay, A. C. (2020) · Psychological Science · doi:10.1177/0956797620922785 · Cited by 28
Metadata
- 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
- 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.
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