Real Solutions for Fake News? Measuring the Effectiveness of General Warnings and Fact-Check Tags in Reducing Belief in False Stories on Social Media
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Research has demonstrated fact-checking's efficacy in helping debunk fake news but also acknowledged that the labor-intensive nature made it challenging to scale.
“Research has demonstrated its efcacy in helping debunk fake news [19,102] but also acknowledged that the labor-intensive nature made it challenging to scale [71].”
From Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions (2023) · cites this paper as [19]
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 [34]
Cites
Social Media and Fake News in the 2016 Election
Allcott, H., & Gentzkow, M. (2017) · Journal of Economic Perspectives · doi:10.1257/jep.31.2.211 · Cited by 6,767 · see citing works
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk
Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012) · Political Analysis · doi:10.1093/pan/mpr057 · Cited by 4,008 · see citing works
Misinformation and Its Correction: Continued Influence and Successful Debiasing
Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012) · Psychological Science in the Public Interest · doi:10.1177/1529100612451018 · Cited by 2,920 · see citing works
Prior exposure increases perceived accuracy of fake news
Pennycook, G., Cannon, T. D., & Rand, D. G. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000465 · Cited by 1,268 · see citing works
Inoculating the Public against Misinformation about Climate Change
van der Linden, S., Leiserowitz, A., Rosenthal, S., & Maibach, E. (2017) · Global Challenges · doi:10.1002/gch2.201600008 · Cited by 1,058 · see citing works
Motivated numeracy and enlightened self-government
KAHAN, D. M., PETERS, E., DAWSON, E. C., & SLOVIC, P. (2017) · Behavioural Public Policy · doi:10.1017/bpp.2016.2 · Cited by 883 · see citing works
Pennycook, G., & Rand, D. G. (2020) · Journal of Personality · doi:10.1111/jopy.12476 · Cited by 879 · see citing works
Perceptions of scientific dissent undermine public support for environmental policy
Aklin, M., & Urpelainen, J. (2014) · Environmental Science & Policy · doi:10.1016/j.envsci.2013.10.006 · Cited by 111 · see citing works
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Using social and behavioural science to support COVID-19 pandemic response
Bavel, J. J. V., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0884-z · Cited by 4,964 · see citing works
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
Pennycook, G., & Rand, D. G. (2020) · Journal of Personality · doi:10.1111/jopy.12476 · Cited by 879 · see citing works
Guess, A. M., Lerner, M., Lyons, B., Montgomery, J. M., Nyhan, B., Reifler, J., & Sircar, N. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1920498117 · Cited by 773 · see citing works
Self-citationFake news, disinformation and misinformation in social media: a review
Aïmeur, E., Amri, S., & Brassard, G. (2023) · Social Network Analysis and Mining · doi:10.1007/s13278-023-01028-5 · Cited by 772 · see citing works
Jones-Jang, S. M., Mortensen, T., & Liu, J. (2021) · American Behavioral Scientist · doi:10.1177/0002764219869406 · Cited by 685 · see citing works
Evaluating the fake news problem at the scale of the information ecosystem
Allen, J., Howland, B., Mobius, M., Rothschild, D., & Watts, D. J. (2020) · Science Advances · doi:10.1126/sciadv.aay3539 · Cited by 528 · see citing works
Social Media, Echo Chambers, and Political Polarization
Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373 · see citing works
All the News That’s Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation
Kreps, S., McCain, R. M., & Brundage, M. (2022) · Journal of Experimental Political Science · doi:10.1017/xps.2020.37 · Cited by 360 · see citing works
Zhou, J., Zhang, Y., Luo, Q., Parker, A. G., & De Choudhury, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581318 · Cited by 288 · see citing works
The Epistemic Threat of Deepfakes
Fallis, D. (2021) · Philosophy & Technology · doi:10.1007/s13347-020-00419-2 · Cited by 266 · see citing works
Bryanov, K., & Vziatysheva, V. (2021) · PLOS ONE · doi:10.1371/journal.pone.0253717 · Cited by 211 · see citing works
Political 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
Vraga, E. K., Kim, S. C., & Cook, J. (2019) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2019.1653102 · Cited by 162 · see citing works
Altay, S., & Gilardi, F. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae403 · Cited by 119 · see citing works
Exposure to social engagement metrics increases vulnerability to misinformation
Avram, M., Micallef, N., Patil, S., & Menczer, F. (2020) · Harvard Kennedy School Misinformation Review · doi:10.37016/mr-2020-033 · Cited by 83 · see citing works
A model of online misinformation
Acemoglu, D., Ozdaglar, A., & Siderius, J. (2024) · Review of Economic Studies · doi:10.1093/restud/rdad111 · Cited by 82 · see citing works
SoK: Content Moderation in Social Media, from Guidelines to Enforcement, and Research to Practice
Singhal, M., Ling, C., Paudel, P., Thota, P., Kumarswamy, N., Stringhini, G., & Nilizadeh, S. (2023) · 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P) · doi:10.1109/eurosp57164.2023.00056 · Cited by 57 · see citing works
Capraro, V., & Celadin, T. (2023) · Personality and Social Psychology Bulletin · doi:10.1177/01461672221117691 · Cited by 49 · see citing works
Exploring the Use of Personalized AI for Identifying Misinformation on Social Media
Jahanbakhsh, F., Katsis, Y., Wang, D., Popa, L., & Muller, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581219 · Cited by 42 · see citing works
Effect of Explanation Conceptualisations on Trust in AI-assisted Credibility Assessment
Pareek, S., van Berkel, N., Velloso, E., & Goncalves, J. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3686922 · Cited by 42 · see citing works
Ternovski, J., Kalla, J., & Aronow, P. M. (2021) · doi:10.31219/osf.io/dta97 · Cited by 37 · see citing works
How Effective Are Interventions Against Misinformation?
Altay, S. (2022) · doi:10.31234/osf.io/sm3vk · Cited by 32 · see citing works
Prominent misinformation interventions reduce misperceptions but increase skepticism
Hoes, E., Aitken, B., Zhang, J., Gackowski, T., & Wojcieszak, M. (2023) · doi:10.31234/osf.io/zmpdu · Cited by 21 · see citing works
Kožuh, I., & Čakš, P. (2023) · Healthcare · doi:10.3390/healthcare11202796 · Cited by 21 · see citing works
Search & Verify: Misinformation and source evaluations in Internet search results
Dennis, A. R., Moravec, P. L., & Kim, A. (2023) · Decision Support Systems · doi:10.1016/j.dss.2023.113976 · Cited by 16 · see citing works
Investigating coordinated account creation using burst detection and network analysis
Bellutta, D., & Carley, K. M. (2023) · Journal of Big Data · doi:10.1186/s40537-023-00695-7 · Cited by 15 · see citing works
Generative AI in the Era of 'Alternative Facts'
Gabriel, S., Lyu, L., Siderius, J., Ghassemi, M., Andreas, J., & Ozdaglar, A. (2024) · An MIT Exploration of Generative AI · doi:10.21428/e4baedd9.82175d26 · Cited by 11 · see citing works
- Authors
- Clayton, K., Blair, S., Busam, J. A., Forstner, S., Glance, J., Green, G., Kawata, A., Kovvuri, A., Martin, J., Morgan, E., Sandhu, M., Sang, R., Scholz-Bright, R., Welch, A. T., Wolff, A. G., Zhou, A., & Nyhan, B.
- Affiliations
- Dartmouth College (US)
- University of Michigan (US)
- Corresponding author
- Nyhan, Brendan
- Venue
- Political Behavior
- Published
- 2019-02-11
- Volume
- 42
- Issue
- 4
- Pages
- 1073-1095
- ISSN
- 0190-9320 (ISSN-L)
- 1573-6687
- OpenAlex
- W2913284693
- Semantic Scholar
- fe31ec84e94712f8c0aedc2ba94233ca025c89f8
- Cited by
- 658
- References
- 8
- Citations by year
- 2026: 58 · 2025: 90 · 2024: 109 · 2023: 122 · 2022: 70 · 2021: 119 · 2020: 79 · 2019: 11
- FWCI
- 140.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Political Behavior (publishedVersion)
- Funders
- Dartmouth College Office of Undergraduate Advising and Research
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Keywords
- fake news, fact-checking, social media misinformation, perceived accuracy, Facebook, partisanship, 2016 US presidential election, countering disinformation
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