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Opinion Diversity and the Resilience of Cooperation in Dynamical Networks

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  • Adam Lee Miles

    (Department of Computing and Mathematics, John R. Dalton Building, All Saints Campus, Manchester M15 6BH, UK)

  • Matteo Cavaliere

    (Department of Computing and Mathematics, John R. Dalton Building, All Saints Campus, Manchester M15 6BH, UK)

Abstract

Across various scenarios, individuals cooperate with others to contribute towards a shared goal and ensure self-preservation. In game theory, the act of cooperation is considered as an individual producing some form of benefit to be utilised by others, under the expectation others will return the favour. In several scenarios, individuals make use of their own information to aid with their decision about who to connect and cooperate with. However, the choice of cooperation can be taken advantage of by opportunistic defectors, which can lead to significant disruption. This paper investigates how the diversity of opinion can contribute to the structure and mechanics of a dynamical network model and to the resilience of cooperation, by utilising a computational model where individuals make use of both public and private information to implement their decision. Our results show that increasing diversity leads to more stable, less connected and less prosperous networks coupled to more frequent, but shallower information cascades. Our work generally shows that the outcome of the conflict between cooperators and cheaters strongly depends on the interplay between population structure, individual decision making and individual opinions.

Suggested Citation

  • Adam Lee Miles & Matteo Cavaliere, 2021. "Opinion Diversity and the Resilience of Cooperation in Dynamical Networks," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:15:p:1801-:d:604219
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    References listed on IDEAS

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    3. Bin Wu & Da Zhou & Feng Fu & Qingjun Luo & Long Wang & Arne Traulsen, 2010. "Evolution of Cooperation on Stochastic Dynamical Networks," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-7, June.
    4. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, October.
    5. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
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