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When Is Society Susceptible to Manipulation?

Author

Listed:
  • Mohamed Mostagir

    (Ross Business School, University of Michigan, Ann Arbor, Michigan 48109)

  • Asuman Ozdaglar

    (Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • James Siderius

    (Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

We consider a social learning model where agents learn about an underlying state of the world from individual observations as well as from exchanging information with each other. A principal (e.g., a firm or a government) interferes with the learning process in order to manipulate the beliefs of the agents. By utilizing the same forces that give rise to the “wisdom of the crowd” phenomenon, the principal can get the agents to take an action that is not necessarily optimal for them but is in the principal’s best interest. We characterize the social norms and network structures that are susceptible to this kind of manipulation and derive conditions under which a social network is impervious and cannot be manipulated. In the process, we develop a new centrality measure and describe how our model offers insights into designing networks that are resistant to manipulation.

Suggested Citation

  • Mohamed Mostagir & Asuman Ozdaglar & James Siderius, 2022. "When Is Society Susceptible to Manipulation?," Management Science, INFORMS, vol. 68(10), pages 7153-7175, October.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:10:p:7153-7175
    DOI: 10.1287/mnsc.2021.4265
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    References listed on IDEAS

    as
    1. Ozan Candogan & Kimon Drakopoulos, 2020. "Optimal Signaling of Content Accuracy: Engagement vs. Misinformation," Operations Research, INFORMS, vol. 68(2), pages 497-515, March.
    2. Qingmin Liu, 2011. "Information Acquisition and Reputation Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(4), pages 1400-1425.
    3. Bohren, Aislinn & Hauser, Daniel, 2017. "Learning with Heterogeneous Misspecified Models: Characterization and Robustness," CEPR Discussion Papers 12036, C.E.P.R. Discussion Papers.
    4. Matthew O. Jackson & Tomas Rodriguez-Barraquer & Xu Tan, 2012. "Social Capital and Social Quilts: Network Patterns of Favor Exchange," American Economic Review, American Economic Association, vol. 102(5), pages 1857-1897, August.
    5. Daron Acemoğlu & Giacomo Como & Fabio Fagnani & Asuman Ozdaglar, 2013. "Opinion Fluctuations and Disagreement in Social Networks," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 1-27, February.
    6. Yiangos Papanastasiou, 2020. "Fake News Propagation and Detection: A Sequential Model," Management Science, INFORMS, vol. 66(5), pages 1826-1846, May.
    Full references (including those not matched with items on IDEAS)

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