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A Model of Online Misinformation

Author

Listed:
  • Daron Acemoglu
  • Asuman Ozdaglar
  • James Siderius

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.

Suggested Citation

  • Daron Acemoglu & Asuman Ozdaglar & James Siderius, 2024. "A Model of Online Misinformation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3117-3150.
    • Handle: RePEc:oup:restud:v:91:y:2024:i:6:p:3117-3150.
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    File URL: http://hdl.handle.net/10.1093/restud/rdad111
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    Cited by:

    1. Leonardo D'Amico & Guido Tabellini, 2022. "Disengaging from Reality - Online Behavior and Unpleasant Political News," CESifo Working Paper Series 9696, CESifo.
    2. Matilde Giaccherini & Joanna Kopinska & Gabriele Rovigatti, 2022. "Vax Populi: The Social Costs of Online Vaccine Skepticism," CESifo Working Paper Series 10184, CESifo.
    3. Daron Acemoglu & Asuman Ozdaglar & James Siderius, 2025. "Artificial Intelligence and Political Economy," NBER Chapters, in: The Economics of Artificial Intelligence: Political Economy, National Bureau of Economic Research, Inc.
    4. Swank, Lotte, 2023. "Vague news and fake news," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 89-106.
    5. Bar Light, 2025. "Computing and Learning Mean Field Equilibria with Scalar Interactions: Algorithms and Applications," Papers 2502.12024, arXiv.org.
    6. Della Lena, Sebastiano, 2024. "The spread of misinformation in networks with individual and social learning," European Economic Review, Elsevier, vol. 168(C).

    More about this item

    Keywords

    Echo chambers; Fake news; Filter bubbles; Homophily; Misinformation; NetworksSocial media;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • P16 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Capitalist Institutions; Welfare State

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