A model of online misinformation
Abstract
Abstract We present a model of online content sharing where agents sequentially observe an article and decide whether to share it with others. This content may or may not contain misinformation. Each agent starts with an ideological bias and gains utility from positive social media interactions but does not want to be called out for propagating misinformation. We characterize the (Bayesian–Nash) equilibria of this social media game and establish that it exhibits strategic complementarities. Under this framework, we study how a platform interested in maximizing engagement would design its algorithm. Our main result establishes that when the relevant articles have low-reliability and are thus likely to contain misinformation, the engagement-maximizing algorithm takes the form of a “filter bubble”—creating an echo chamber of like-minded users. Moreover, filter bubbles become more likely when there is greater polarization in society and content is more divisive. Finally, we discuss various regulatory solutions to such platform-manufactured misinformation.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
This strategy places a premium on user attention, which has led companies to deploy AI and machine learning techniques to prolong user engagement, often to the detriment of individual and societal well-being.
“This strategy places a premium on user attention, which has led companies to deploy AI and machine learning techniques to prolong user engagement, often to the detriment of individual and societal well-being (12–15).”
From The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024) · cites this paper as [13]
Cites
The spread of true and false news online
Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847 · cited 2× · see citing works
“Despite this observation, other works such as Vosoughi et al. (2018) document that misinformation spreads farther, faster, deeper, and more broadly than truthful news on social media.”
BackgroundSocial 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
A Simple Model of Herd Behavior
Banerjee, A. V. (1992) · The Quarterly Journal of Economics · doi:10.2307/2118364 · Cited by 6,556 · see citing works
(2011) · Cited by 4,430 · see citing works
Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., et al. (2018) · Science · doi:10.1126/science.aao2998 · Cited by 4,160 · see citing works
A lattice-theoretical fixpoint theorem and its applications
Tarski, A. (1955) · Pacific Journal of Mathematics · doi:10.2140/pjm.1955.5.285 · Cited by 2,745 · see citing works
The spread of behavior in an online social network experiment
Centola, D. (2010) · Science · doi:10.1126/science.1185231 · Cited by 2,692 · see citing works
The spreading of misinformation online
Del Vicario, M., Bessi, A., Zollo, F., Petroni, F., Scala, A., Caldarelli, G., Stanley, H. E., & Quattrociocchi, W. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517441113 · Cited by 2,407 · see citing works
Supermodularity and Complementarity
Topkis, D. M. (2011) · Princeton University Press eBooks · doi:10.1515/9781400822539 · Cited by 2,254 · see citing works
Pennycook, G., & Rand, D. G. (2019) · Cognition · doi:10.1016/j.cognition.2018.06.011 · Cited by 2,022 · see citing works
Complex Contagions and the Weakness of Long Ties
Centola, D., & Macy, M. (2007) · American Journal of Sociology · doi:10.1086/521848 · Cited by 1,878 · see citing works
Fake news on Twitter during the 2016 U.S. presidential election
Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019) · Science · doi:10.1126/science.aau2706 · Cited by 1,803 · see citing works
Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020) · Psychological Science · doi:10.1177/0956797620939054 · Cited by 1,715 · see citing works
Less than you think: Prevalence and predictors of fake news dissemination on Facebook
Guess, A., Nagler, J., & Tucker, J. (2019) · Science Advances · doi:10.1126/sciadv.aau4586 · Cited by 1,652 · see citing works
Gentzkow, M., & Kamenica, E. (2024) · World Scientific Series in Economic Theory · doi:10.1257/aer.101.6.2590 · Cited by 1,536 · see citing works
Gentzkow, M., & Shapiro, J. M. (2006) · Journal of Political Economy · doi:10.1086/499414 · Cited by 1,274 · 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 · cited 1× · see citing works
“For example, see https://www.snopes.com/fact-check/mass-shootings-under-trump/ and Greene et al. (2021) and Garimella and Eckles (2020).”
BackgroundShifting attention to accuracy can reduce misinformation online
Pennycook, G., Epstein, Z., Mosleh, M., Arechar, A. A., Eckles, D., & Rand, D. G. (2021) · Nature · doi:10.1038/s41586-021-03344-2 · Cited by 1,155 · see citing works
Media and Political Polarization
Prior, M. (2013) · Annual Review of Political Science · doi:10.1146/annurev-polisci-100711-135242 · Cited by 1,125 · see citing works
Naïve Learning in Social Networks and the Wisdom of Crowds
Golub, B., & Jackson, M. O. (2010) · American Economic Journal Microeconomics · doi:10.1257/mic.2.1.112 · Cited by 1,036 · see citing works
Algorithmic regulation: A critical interrogation
Yeung, K. (2018) · Regulation & Governance · doi:10.1111/rego.12158 · Cited by 842 · see citing works
Bala, V., & Goyal, S. (1998) · The Review of Economic Studies · doi:10.1111/1467-937x.00059 · Cited by 777 · see citing works
Pennycook, G., Bear, A., Collins, E., & Rand, D. G. (2020) · Management Science · doi:10.1287/mnsc.2019.3478 · Cited by 718 · see citing works
Clayton, K., Blair, S., Busam, J. A., Forstner, S., Glance, J., Green, G., Kawata, A., Kovvuri, A., Martin, J., Morgan, E., et al. (2020) · Political Behavior · doi:10.1007/s11109-019-09533-0 · Cited by 658 · see citing works
Fake news as a two-dimensional phenomenon: a framework and research agenda
Egelhofer, J. L., & Lecheler, S. K. (2019) · Annals of the International Communication Association · doi:10.1080/23808985.2019.1602782 · Cited by 655 · see citing works
Social Media, News Consumption, and Polarization: Evidence from a Field Experiment
Levy, R. (2021) · American Economic Review · doi:10.1257/aer.20191777 · Cited by 624 · see citing works
Guess, A. M., Nyhan, B. J., & Reifler, J. (2018) · Cited by 544 · 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
“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content
Molina, M. D., Sundar, S. S., Le, T., & Lee, D. (2021) · American Behavioral Scientist · doi:10.1177/0002764219878224 · Cited by 485 · see citing works
Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools
Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020) · Psychological Science in the Public Interest · doi:10.1177/1529100620946707 · Cited by 479 · see citing works
Spread of (mis)information in social networks
Acemoglu, D., Ozdaglar, A., & ParandehGheibi, A. (2010) · Games and Economic Behavior · doi:10.1016/j.geb.2010.01.005 · Cited by 444 · see citing works
Echo chambers and viral misinformation: Modeling fake news as complex contagion
Törnberg, P. (2018) · PLoS ONE · doi:10.1371/journal.pone.0203958 · Cited by 430 · see citing works
Bayesian Persuasion and Information Design
Kamenica, E. (2019) · Annual Review of Economics · doi:10.1146/annurev-economics-080218-025739 · Cited by 424 · see citing works
Polarization in the American Public: Misconceptions and Misreadings
Fiorina, M. P., Abrams, S. A., & Pope, J. C. (2008) · The Journal of Politics · doi:10.1017/s002238160808050x · Cited by 414 · see citing works
Opinion Fluctuations and Disagreement in Social Networks
Acemoğlu, D., Como, G., Fagnani, F., & Ozdaglar, A. (2012) · Mathematics of Operations Research · doi:10.1287/moor.1120.0570 · Cited by 408 · see citing works
The Disappearing Center: Engaged Citizens, Polarization, and American Democracy
Han, H. (2011) · Public Opinion Quarterly · doi:10.1093/poq/nfr042 · Cited by 382 · see citing works
Why do so few people share fake news? It hurts their reputation
Altay, S., Hacquin, A.-S., & Mercier, H. (2020) · New Media & Society · doi:10.1177/1461444820969893 · Cited by 244 · see citing works
Demortain, D., & Benbouzid, B. (2019) · doi:10.1093/oso/9780198838494.001.0001 · Cited by 146 · see citing works
Fragility of asymptotic agreement under Bayesian learning
Acemoğlu, D., Chernozhukov, V., & Yıldız, M. (2016) · Theoretical Economics · doi:10.3982/te436 · Cited by 142 · see citing works
Estimating peer effects in networks with peer encouragement designs
Eckles, D., Kizilcec, R. F., & Bakshy, E. (2016) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1511201113 · Cited by 141 · see citing works
Fake News Propagation and Detection: A Sequential Model
Papanastasiou, Y. (2020) · Management Science · doi:10.1287/mnsc.2019.3295 · Cited by 131 · see citing works
Shared partisanship dramatically increases social tie formation in a Twitter field experiment
Mosleh, M., Martel, C., Eckles, D., & Rand, D. G. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2022761118 · Cited by 123 · see citing works
Social media and microtargeting: Political data processing and the consequences for Germany
Papakyriakopoulos, O., Hegelich, S., Shahrezaye, M., & Serrano, J. C. M. (2018) · Big Data & Society · doi:10.1177/2053951718811844 · Cited by 121 · see citing works
Social influence maximization under empirical influence models
Aral, S., & Dhillon, P. S. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0346-z · Cited by 109 · see citing works
Optimal Signaling of Content Accuracy: Engagement vs. Misinformation
Candogan, O., & Drakopoulos, K. (2020) · Operations Research · doi:10.1287/opre.2019.1897 · Cited by 73 · see citing works
Greene, C. M., Nash, R. A., & Murphy, G. (2021) · Memory · doi:10.1080/09658211.2021.1923754 · Cited by 67 · see citing works
Why Do People Share Political Information on Social Media?
Kim, D. H., Jones-Jang, S. M., & Kenski, K. M. (2020) · Digital Journalism · doi:10.1080/21670811.2020.1827966 · Cited by 43 · see citing works
Seeding the Herd: Pricing and Welfare Effects of Social Learning Manipulation
Chen, L., & Papanastasiou, Y. (2021) · Management Science · doi:10.1287/mnsc.2020.3849 · Cited by 33 · see citing works
Social Inequality and the Spread of Misinformation
Mostagir, M., & Siderius, J. (2022) · Management Science · doi:10.1287/mnsc.2022.4380 · Cited by 28 · see citing works
When Is Society Susceptible to Manipulation?
Mostagir, M., Ozdaglar, A., & Siderius, J. (2022) · Management Science · doi:10.1287/mnsc.2021.4265 · Cited by 24 · see citing works
Learning in a Post-Truth World
Mostagir, M., & Siderius, J. (2022) · Management Science · doi:10.1287/mnsc.2022.4340 · Cited by 24 · see citing works
Information Inundation on Platforms and Implications
Allon, G., Drakopoulos, K., & Manshadi, V. (2021) · Operations Research · doi:10.1287/opre.2021.2119 · Cited by 15 · see citing works
Merlino, L. P., Pin, P., & Tabasso, N. (2023) · American Economic Journal Microeconomics · doi:10.1257/mic.20200403 · Cited by 13 · see citing works
Learning Manipulation Through Information Dissemination
Keppo, J., Kim, M. J., & Zhang, X. (2019) · Operations Research · doi:10.1287/opre.2021.2209 · Cited by 13 · see citing works
Regulating algorithmic filtering on social mediaPreprint
Cen, S. H., & Devavrat Shah, B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.09647 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae191 · Cited by 371 · see citing works
Content moderation and advertising in social media platforms
Madio, L., & Quinn, M. (2024) · Journal of Economics & Management Strategy · doi:10.1111/jems.12602 · Cited by 45 · see citing works
The impact of generative artificial intelligence on socioeconomic inequalities and policy makingPreprint
Capraro, V., Lentsch, A., Acemoğlu, D., Akgün, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas‐Garza, P., Butera, L., Douglas, K. M., et al. (2023) · doi:10.31234/osf.io/6fd2y · Cited by 36 · see citing works
Curtailing False News, Amplifying Truth
Guriev, S. M., Henry, E., Marquis, T., & Zhuravskaya, E. V. (2026) · Econometrica · doi:10.3982/ecta22524 · Cited by 16 · see citing works
Misinformation Due to Asymmetric Information Sharing
Buechel, B., Klößner, S., Meng, F., & Nassar, A. (2022) · Journal of Economic Dynamics and Control · doi:10.1016/j.jedc.2023.104641 · Cited by 15 · see citing works
Ranking for engagement: How social media algorithms fuel misinformation and polarization
Germano, F., Gómez, V., & Sobbrio, F. (2026) · Journal of Public Economics · doi:10.1016/j.jpubeco.2026.105589 · Cited by 14 · see citing works
The Impact of Generative Artificial Intelligence on Socioeconomic Inequalities and Policy MakingPreprint
Capraro, V., Lentsch, A., Acemoğlu, D., Akgün, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas‐Garza, P., Butera, L., Douglas, K. M., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4666103 · Cited by 13 · see citing works
The Economics of Social MediaPreprint
Aridor, G., Durán, R. J., Levy, R., & Song, L. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4708840 · Cited by 12 · see citing works
The rise of authoritarian informationalism: escalating surveillance, manipulation, and control
Garbe, L., & Maerz, S. F. (2026) · Democratization · doi:10.1080/13510347.2025.2579105 · Cited by 11 · see citing works
Robust Content Moderation: Theory and Applications
Kominers, S. D., & Shapiro, J. M. (2024) · National Bureau of Economic Research · doi:10.3386/w32156 · Cited by 10 · see citing works
AI and Social Media: A Political Economy Perspective
Acemoglu, D., Ozdaglar, A., & Siderius, J. (2025) · doi:10.3386/w33892 · Cited by 9 · see citing works
Stone, D. F. (2023) · The MIT Press eBooks · doi:10.7551/mitpress/14496.001.0001 · Cited by 8 · see citing works
Social Learning Under Platform Influence: Consensus and Persistent DisagreementPreprint
Candogan, O., Immorlica, N., Light, B., & Anunrojwong, J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3675712 · Cited by 8 · see citing works
Misinformation, Narratives, and Intergroup Attitudes: Evidence from India
Daxecker, U., Fjelde, H., & Prasad, N. (2024) · The Journal of Politics · doi:10.1086/732979 · Cited by 6 · see citing works
Digital divide and artificial intelligence for health
Jean, C., Bussotti, J.-F., Grazia, C., Omrani, N., & Papotti, P. (2025) · Technovation · doi:10.1016/j.technovation.2025.103392 · Cited by 7 · see citing works
Misinformation in Social Media: The Role of Verification IncentivesPreprint
Cisternas, G., & Vasquez, J. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4191785 · Cited by 5 · see citing works
Are Social Media Platforms a Threat to Democracy? An Ecosystem Governance Perspective
Cennamo, C., & Karanović, J. (2026) · Journal of Management Studies · doi:10.1111/joms.70044 · Cited by 4 · see citing works
A Game-Theoretic Model of Misinformation Spread on Social Networks
Hsu, C.-C., Ajorlou, A., & Jadbabaie, A. (2024) · Games and Economic Behavior · doi:10.1016/j.geb.2025.07.007 · Cited by 4 · see citing works
Disengaging from Reality – Online Behavior and Unpleasant Political NewsPreprint
D'Amico, L., & Tabellini, G. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4087951 · Cited by 4 · see citing works
Petrova, M., & Tapsoba, A. (2025) · Economic Policy · doi:10.1093/epolic/eiaf012 · Cited by 3 · see citing works
Vacarelu, M. T. (2023) · Springer eBooks · doi:10.1007/978-3-031-22552-9_8 · Cited by 3 · see citing works
Troll FarmsPreprint
Denter, P., & Ginzburg, B. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3919032 · Cited by 3 · see citing works
The Attention-Information Trade-Off
Serra-García, M. (2026) · American Economic Review · doi:10.1257/aer.20240850 · Cited by 2 · see citing works
Gatti, D., Lô, G. D., & Serranito, F. (2025) · Ecological Economics · doi:10.1016/j.ecolecon.2025.108826 · Cited by 2 · see citing works
Modeling misinformation spread for policy evaluation: a parsimonious framework
Deng, Y., & Staelin, R. (2024) · Marketing Letters · doi:10.1007/s11002-024-09724-8 · Cited by 2 · see citing works
Social Learning and Content Quality Under Polarization
Kadiyala, B., & Shin, D. (2024) · Manufacturing & Service Operations Management · doi:10.1287/msom.2022.0533 · Cited by 2 · see citing works
Disengaging from Reality: Online Behavior and Unpleasant Political NewsPreprint
D'Amico, L., & Tabellini, G. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4305223 · Cited by 2 · see citing works
Will Nation States Reassert Their Sovereignty over the Platform Economy?Preprint
Calvo, A. G., Kenney, M. F., & Zysman, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4790191 · Cited by 2 · see citing works
(Pro-)Social Learning and Strategic DisclosurePreprint
Bénabou, R., & Vellodi, N. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4827818 · Cited by 2 · see citing works
GenAI Misinformation, Trust, and News Consumption: Evidence from a Field Experiment
Campante, F. R., Durante, R., Hagemeister, F., & Sen, A. (2025) · National Bureau of Economic Research · doi:10.3386/w34100 · Cited by 3 · see citing works
Homophily and spread of misinformation in random networks
Gong, Q., & Yang, H. (2024) · Economic Theory · doi:10.1007/s00199-024-01619-z · Cited by 1 · see citing works
Communication experiment with moral-based chatbot: toward solution of divisions in democracy
Miwa, K., Yamakawa, M., Nakahara, A., & Shimada, A. K. (2025) · Ai & Society · doi:10.1007/s00146-025-02377-9 · Cited by 2 · see citing works
Transparent Tagging for Strategic Social Nudges on User-Generated Misinformation
Yang, Y.-T. C., Li, T., & Zhu, Q. (2025) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2025.3591983 · Cited by 1 · see citing works
AI Agents and the Progressive Intermediation Between Users and Online Services: A Critical Analysis
Rondina, M., Vetrò, A., Martin, J. C. D., Bargis, M., & Elia, G. (2026) · Future Internet · doi:10.3390/fi18080419 · Cited by 1 · see citing works
Content Filtering with Inattentive Information Consumers
Ball, I., Bono, J. W., Grana, J., Immorlica, N., Lucier, B., & Slivkins, A. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i9.28803 · Cited by 1 · see citing works
Online Business Models, Digital Ads, and User Welfare
Acemoğlu, D., Huttenlocher, D. P., Ozdaglar, A., & Siderius, J. (2026) · Journal of Political Economy · doi:10.1086/742715 · Cited by 1 · see citing works
Subscription Networks, Verification, and Media BiasPreprint
Hsu, C.-C., Ajorlou, A., Yıldız, M., & Jadbabaie, A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4263099 · Cited by 1 · see citing works
Ranking for Engagement: How Social Media Algorithms Fuel Misinformation and PolarizationPreprint
Germano, F., Gómez, V., & Sobbrio, F. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4238756 · Cited by 1 · see citing works
Asymmetric Content Moderation in Search Markets: The Case of Adult Websites
Madio, L., Mitchell, M. F., Quinn, M., & Reggiani, C. (2026) · CESifo · doi:10.65864/pdivjbfpzc · Cited by 1 · see citing works
Computing and Learning Mean Field Equilibria with Scalar Interactions: Algorithms and ApplicationsPreprint
Light, B. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5123882 · Cited by 1 · see citing works
Headlines as Truncated ExperimentsPreprint
Wu, J., & Nachbar, J. H. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3375352
Ranking for Engagement: How Social Media Algorithms Fuel Misinformation and PolarizationPreprint
Germano, F., Gómez, V., & Sobbrio, F. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4257210
Strategic Management of Social InformationPreprint
Reggiani, C., Saporiti, A., & Simanjuntak, L. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4434685
The power of good neighbors: An analysis of intergenerational mobilityPreprint
MENDOZA, R. A. M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4633187
The Economics of Social MediaPreprint
Aridor, G., Jiménez-Durán, R., Levy, R., & Song, L. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4723727
Optimal Verification of Rumors in NetworksPreprint
Merlino, L. P., & Tabasso, N. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4873554
Price of Censorship of a Policy Removing Misinformation in a Social Network
Petithomme, J., Touati, C., & Bravard, C. (2024) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton63246.2024.10735296
Spewing Hate or Speaking Tolerance: How Free Speech Affects Social Norms and Minority RightsPreprint
Williamson, C. R. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4986698
An evidence-accumulating drift–diffusion model of competing information spread on networks
Corsin, J., Zino, L., & Ye, M. (2025) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2024.115935
Spewing Hate or Speaking Tolerance: How Free Speech Affects Social Norms and Minority RightsPreprint
Williamson, C. R. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5135017
Misinformation vs. Truth: Information Diffusion Dynamics on Social MediaPreprint
Guo, W. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5089043
Levi, E., Bayerlein, M., Grimalda, G. F., & Reggiani, T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5167714
Asymmetric Content Moderation in Search Markets: The Case of Adult WebsitesPreprint
Madio, L., Mitchell, M. F., Quinn, M., & Reggiani, C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5239051
The Twin Disruption of Generative AI: Unbundling Capability and Responsibility in Creative WorkPreprint
Walkowiak, E., & Potts, J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5362872
Influence and Counter-Influence in NetworksPreprint
Sudipta Sarangi, B., Bravard, C., Durieu, J., & Touati, C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5370776
The Evolution of Research on the Digital EconomyPreprint
Kaiser, F. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5399959
Leippold, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5406124
(Pro-)Social Learning and Strategic Disclosure
Bénabou, R., & Vellodi, N. (2025) · American Economic Journal Microeconomics · doi:10.1257/mic.20240190
Gate-Elastic Mechanisms for Human-AI VerificationPreprint
Leippold, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5553860
Polarization as Pluralistic Ignorance
Asami, K., & Kishishita, D. (2025) · Journal of Public Economic Theory · doi:10.1111/jpet.70076
False Cascades and the Cost of TruthPreprint
Cheredina, D., & Lukyanov, G. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5801559
Belief-Behavior Feedback, Cascade, and Optimal Platform InterventionPreprint
Li, Y., Fabrizi, S., & Lippert, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5883963
Echo Chamber Dynamics in LLMs: Mitigating Bias and Model Drift
Rutherford, D., & Wu, N. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-12313-8_4
Distributed Optimal Solution Manipulated via Local False Information
Zhu, W., & Hong, Y. (2026) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2026.3660188
The consumer and the chamber of selective information: the upside of higher prices in online markets
Bakó, B., & Kálecz‐Simon, A. (2026) · Electronic Commerce Research · doi:10.1007/s10660-026-10106-7
Content Moderation and Adverse Selection in the Digital Marketplace of Ideas: Evidence from BrazilPreprint
de Oliveira, C. A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6250731
Sharing Opinions in the Shadow of AIPreprint
Ash, E., Lou, Y., & Song, L. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6432959
Reducing misinformation on social media: an experimental evaluation of two policy interventions
Rentschler, L., & Samad, Z. (2025) · Experimental Economics · doi:10.1017/eec.2026.10040
Social Media CommentsPreprint
Donati, D., & Song, L. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6529698
Adaptive Boundary-Aware Fact-Checker Placement for Misinformation Suppression in Social Networks
Firouzjaee, M. T., Naderi, G., Gore, R. J., & Moghim, N. (2026) · Applied Sciences · doi:10.3390/app16104740
Zhong, Z. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6806438
Lecorps, Y., Obidzinski, M., & Oytana, Y. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6999286
Platform Marketing: Theory and Design
Zhou, B. (2026) · doi:10.1093/9780197859063.003.0040
Centrality in Normalized Stochastic Networks
Mostagir, M., & Siderius, J. (2026) · Mathematics of Operations Research · doi:10.1287/moor.2024.0528
The Habeas Mentem Principle. Reframing Neurorights in the Digital Age
Giacomini, G. (2026) · Neuroethics · doi:10.1007/s12152-026-09661-5
Whom Should a Platform Amplify? Truth, Engagement, and Networked Polarization *Preprint
Hakobyan, Z. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7098702
Lu, Y., & Zhou, Y. (2026) · SHS Web of Conferences · doi:10.1051/shsconf/202623603007
Zou, F., Wu, D., & Zhao, L. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7372038
A theory of conspiracy theories
Cevik, S. (2026) · Public Choice · doi:10.1007/s11127-026-01443-0
Gan, T. (2026) · Corporate Governance An International Review · doi:10.1111/corg.70065
Krishnan, S. (2026) · International Review of Economics & Finance · doi:10.1016/j.iref.2026.105906
- Authors
- Acemoglu, D., Ozdaglar, A., & Siderius, J.
- Affiliations
- Massachusetts Institute of Technology, NBER, and CEPR ,
- Massachusetts Institute of Technology (US)
- Dartmouth College (US)
- Corresponding author
- Siderius, James
- Venue
- Review of Economic Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-12-12
- Volume
- 91
- Issue
- 6
- Pages
- 3117-3150
- ISSN
- 0034-6527 (ISSN-L)
- 1467-937X
- OpenAlex
- W4389606860
- Cited by
- 82
- References
- 56
- Citations by year
- 2026: 26 · 2025: 24 · 2024: 17 · 2023: 5 · 2022: 7 · 2021: 1 · 2020: 1 · 2019: 1
- FWCI
- 31.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Review of Economic Studies (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Social Sciences › Communication › Social Media and Politics
- Keywords
- online misinformation, content sharing, social media, Bayesian Nash equilibrium, strategic complementarity, filter bubbles, echo chambers, ideological bias, polarization, content reliability, misinformation regulation
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 ›
Are you an author, or do you see a problem with this page? Request a review
