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Learning from Shared News: When Abundant Information Leads to Belief Polarization

Author

Listed:
  • Renee Bowen
  • Danil Dmitriev
  • Simone Galperti

Abstract

We study learning via shared news. Each period agents receive the same quantity and quality of first-hand information and can share it with friends. Some friends (possibly few) share selectively, generating heterogeneous news diets across agents akin to echo chambers. Agents are aware of selective sharing and update beliefs by Bayes' rule. Contrary to standard learning results, we show that beliefs can diverge in this environment leading to polarization. This requires that (i) agents hold misperceptions (even minor) about friends' sharing and (ii) information quality is sufficiently low. Polarization can worsen when agents' social connections expand. When the quantity of first-hand information becomes large, agents can hold opposite extreme beliefs resulting in severe polarization. We find that news aggregators can curb polarization caused by news sharing. Our results hold without media bias or fake news, so eliminating these is not sufficient to reduce polarization. When fake news is included, it can lead to polarization but only through misperceived selective sharing. We apply our theory to shed light on the evolution of public opinions about climate change in the US.

Suggested Citation

  • Renee Bowen & Danil Dmitriev & Simone Galperti, 2021. "Learning from Shared News: When Abundant Information Leads to Belief Polarization," NBER Working Papers 28465, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28465
    Note: POL
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    Citations

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    Cited by:

    1. Marcos Ross Fernandes, 2023. "Confirmation Bias in Social Networks," Working Papers, Department of Economics 2023_02, University of São Paulo (FEA-USP).
    2. repec:zbw:bofrdp:2022_005 is not listed on IDEAS
    3. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Research Discussion Papers 5/2020, Bank of Finland.
    4. Eguia, Jon & Hu, Tai-Wei, 2022. "Voter Polarization and Extremism," Working Papers 2022-5, Michigan State University, Department of Economics.
    5. Gonzalo Cisternas & Jorge Vásquez, 2022. "Misinformation in Social Media: The Role of Verification Incentives," Staff Reports 1028, Federal Reserve Bank of New York.
    6. Eugenio Levi & Michael Bayerlein & Gianluca Grimalda & Tommaso Reggiani, 2023. "Narratives on migration and political polarization: How the emphasis in narratives can drive us apart," MUNI ECON Working Papers 2023-07, Masaryk University.
    7. Ambrocio, Gene & Hasan, Iftekhar, 2022. "Belief polarization and Covid-19," Bank of Finland Research Discussion Papers 10/2022, Bank of Finland.
    8. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    9. Marcos R. Fernandes, 2022. "Confirmation Bias in Social Networks," Papers 2207.12594, arXiv.org, revised Feb 2023.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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