IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/124953.html

Biased Information and Opinion Polarisation

Author

Listed:
  • Suen, Richard M. H.

Abstract

Why do people form polarised opinions after receiving the same information? Why does disagreement persist even when public information is abundant? We show that a Bayesian model with potentially biased public signals can answer these questions. When agents are uncertain and disagree about the bias in the signals, persistent disagreement and opinion polarisation can readily emerge. This happens because uncertainty surrounding the bias Induces agents with diverse initial beliefs to form drastically different posterior estimates. Prolonged exposure to these signals can in some cases drive the agents' opinions further away from each other and also further away from the truth.

Suggested Citation

  • Suen, Richard M. H., 2025. "Biased Information and Opinion Polarisation," MPRA Paper 124953, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:124953
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/124953/1/MPRA_paper_124953.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Péter Kondor, 2012. "The More We Know about the Fundamental, the Less We Agree on the Price," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1175-1207.
    2. Aytimur, R. Emre & Suen, Richard M. H., 2024. "Information Quality, Disagreement and Political Polarisation," MPRA Paper 121112, University Library of Munich, Germany.
    3. Sandeep Baliga & Eran Hanany & Peter Klibanoff, 2013. "Polarization and Ambiguity," American Economic Review, American Economic Association, vol. 103(7), pages 3071-3083, December.
    4. Garz, Marcel & Sood, Gaurav & Stone, Daniel F. & Wallace, Justin, 2020. "The supply of media slant across outlets and demand for slant within outlets: Evidence from US presidential campaign news," European Journal of Political Economy, Elsevier, vol. 63(C).
    5. Paul Heidhues & Botond Kőszegi & Philipp Strack, 2018. "Unrealistic Expectations and Misguided Learning," Econometrica, Econometric Society, vol. 86(4), pages 1159-1214, July.
    6. , & , & ,, 2016. "Fragility of asymptotic agreement under Bayesian learning," Theoretical Economics, Econometric Society, vol. 11(1), January.
    7. Annie Liang & Xiaosheng Mu, 2020. "Complementary Information and Learning Traps," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(1), pages 389-448.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Benoît, Jean-Pierre & Dubra, Juan, 2014. "A Theory of Rational Attitude Polarization," MPRA Paper 60129, University Library of Munich, Germany.
    2. Jean-Pierre Beno t & Juan Dubra, 2018. "When do populations polarize? An explanation," Documentos de Trabajo/Working Papers 1801, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    3. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    4. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Misinterpreting Others and the Fragility of Social Learning," Econometrica, Econometric Society, vol. 88(6), pages 2281-2328, November.
    5. Stone, Daniel, 2018. "Just a big misunderstanding? Bias and Bayesian affective polarization," SocArXiv 58sru, Center for Open Science.
    6. Le Yaouanq, Yves, 2023. "A model of voting with motivated beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 394-408.
    7. Anderson, Axel & Pkhakadze, Nikoloz, 2025. "Polarizing persuasion," Games and Economic Behavior, Elsevier, vol. 152(C), pages 181-198.
    8. Hestermann, Nina & Le Yaouanq, Yves, 2018. "It\'s not my Fault! Self-Confidence and Experimentation," Rationality and Competition Discussion Paper Series 124, CRC TRR 190 Rationality and Competition.
    9. Le Yaouanq, Yves, 2018. "A Model of Ideological Thinking," Rationality and Competition Discussion Paper Series 85, CRC TRR 190 Rationality and Competition.
    10. Jeong, Daeyoung, 2019. "Using cheap talk to polarize or unify a group of decision makers," Journal of Economic Theory, Elsevier, vol. 180(C), pages 50-80.
    11. Tuval Danenberg, 2025. "Bayesian Polarization," Papers 2509.02513, arXiv.org.
    12. Fudenberg, Drew & Lanzani, Giacomo & Strack, Philipp, 2023. "Pathwise concentration bounds for Bayesian beliefs," Theoretical Economics, Econometric Society, vol. 18(4), November.
    13. Goldstein, Itay & Yang, Liyan, 2019. "Good disclosure, bad disclosure," Journal of Financial Economics, Elsevier, vol. 131(1), pages 118-138.
    14. Aytimur, R. Emre & Suen, Richard M. H., 2024. "Information Quality, Disagreement and Political Polarisation," MPRA Paper 121112, University Library of Munich, Germany.
    15. Gabriel Martinez & Nicholas H. Tenev, 2020. "Optimal Echo Chambers," Papers 2010.01249, arXiv.org, revised Jun 2025.
    16. Little, Andrew T. & Moore, Don A & Augenblick, Ned & Backus, Matthew, 2025. "Assumptions, Disagreement, and Overprecision: Theory and Evidence," OSF Preprints mnv4k_v1, Center for Open Science.
    17. Chen, Daniel L. & Levonyan, Vardges & Yeh, Susan, 2016. "Policies Affect Preferences: Evidence from Random Variation in Abortion Jurisprudence," IAST Working Papers 16-58, Institute for Advanced Study in Toulouse (IAST).
    18. Pons Rotger, Gabriel & Rosholm, Michael, 2020. "The Role of Beliefs in Long Sickness Absence: Experimental Evidence from a Psychological Intervention," IZA Discussion Papers 13582, Institute of Labor Economics (IZA).
    19. Hefeker, Carsten, 2022. "Policy coordination under model disagreement and asymmetric shocks," Economic Modelling, Elsevier, vol. 114(C).
    20. Castagnetti, Alessandro & Schmacker, Renke, 2022. "Protecting the ego: Motivated information selection and updating," European Economic Review, Elsevier, vol. 142(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:124953. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.