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Opinion Dynamics with Confirmation Bias

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  • Armen E Allahverdyan
  • Aram Galstyan

Abstract

Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science. Methodology/Principal Findings: We formulate a (non-Bayesian) model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect–when consecutively exposed to two opinions, the preference is given to the last opinion (recency) or the first opinion (primacy) –and relates recency to confirmation bias. Finally, we study the model in the case of repeated persuasion and analyze its convergence properties. Conclusions: The standard Bayesian approach to probabilistic opinion revision is inadequate for describing the observed phenomenology of persuasion process. The simple non-Bayesian model proposed here does agree with this phenomenology and is capable of reproducing a spectrum of effects observed in psychology: primacy-recency phenomenon, boomerang effect and cognitive dissonance. We point out several limitations of the model that should motivate its future development.

Suggested Citation

  • Armen E Allahverdyan & Aram Galstyan, 2014. "Opinion Dynamics with Confirmation Bias," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-14, July.
    • Handle: RePEc:plo:pone00:0099557
    DOI: 10.1371/journal.pone.0099557
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    References listed on IDEAS

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    1. Akerlof, George A & Dickens, William T, 1982. "The Economic Consequences of Cognitive Dissonance," American Economic Review, American Economic Association, vol. 72(3), pages 307-319, June.
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    Cited by:

    1. Riazi, Diana & Livan, Giacomo, 2024. "Public and private beliefs under disinformation in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    3. Cattaneo, Cristina & Grieco, Daniela, 2021. "Turning opposition into support to immigration: The role of narratives," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 785-801.
    4. Fernandes, Marcos R., 2023. "Confirmation bias in social networks," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 59-76.
    5. Antonio Parravano & Ascensión Andina-Díaz & Miguel A Meléndez-Jiménez, 2016. "Bounded Confidence under Preferential Flip: A Coupled Dynamics of Structural Balance and Opinions," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-23, October.
    6. Han, Wenchen & Gao, Shun & Huang, Changwei & Yang, Junzhong, 2022. "Non-consensus states in circular opinion model with repulsive interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    7. Douglas Lee & Jean Daunizeau, 2020. "Choosing what we like vs liking what we choose: How choice-induced preference change might actually be instrumental to decision-making," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-15, May.
    8. Qian, Shen & Liu, Yijun & Galam, Serge, 2015. "Activeness as a key to counter democratic balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 187-196.
    9. Oestereich, André L. & Crokidakis, Nuno & Cajueiro, Daniel O., 2022. "Impact of memory and bias in kinetic exchange opinion models on random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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