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Boundedly rational opinion dynamics in social networks: Does indegree matter?

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  • Battiston, Pietro
  • Stanca, Luca

Abstract

This paper investigates opinion dynamics and social influence in directed communication networks. We study the theoretical properties of a boundedly rational model of opinion formation in which individuals aggregate the information they receive from their neighbors by using weights that are a function of neighbors’ indegree. We then present the results of a laboratory experiment explicitly designed to test the causal effect of indegree on social influence. We find that the social influence of an agent is positively affected by the number of individuals she listens to. When forming their opinions, agents take into account the structure of their communication network, although only to a limited extent.

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  • Battiston, Pietro & Stanca, Luca, 2015. "Boundedly rational opinion dynamics in social networks: Does indegree matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 400-421.
  • Handle: RePEc:eee:jeborg:v:119:y:2015:i:c:p:400-421
    DOI: 10.1016/j.jebo.2015.08.013
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    Cited by:

    1. Bashari, Masoud & Akbarzadeh-T, Mohammad-R., 2020. "Controlling opinions in Deffuant model by reconfiguring the network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    2. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    3. Battiston, Pietro & Harrison, Sharon G., 2024. "Believe it or not: Experimental evidence on sunspot equilibria with social networks," Games and Economic Behavior, Elsevier, vol. 143(C), pages 223-247.
    4. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2023. "Optimal interventions in networks during a pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 847-883, April.
    5. Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    6. Pongou, Roland & Sidie, Ghislain Junior & Tchuente, Guy & Tondji, Jean-Baptiste, 2022. "Profits, Pandemics, and Lockdown Effectiveness in Nursing Home Networks," GLO Discussion Paper Series 1131, Global Labor Organization (GLO).
    7. Brandts, Jordi & Giritligil, Ayça Ebru & Weber, Roberto A., 2015. "An experimental study of persuasion bias and social influence in networks," European Economic Review, Elsevier, vol. 80(C), pages 214-229.
    8. Wang, Zongrun & Chen, Songsheng, 2019. "Market efficiency, strategies and incomes of heterogeneously informed investors in a social network environment," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 15-32.
    9. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    10. Goldbaum David, 2019. "Conformity and Influence," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 19(1), pages 1-29, January.
    11. Berno Buechel & Stefan Klößner & Martin Lochmüller & Heiko Rauhut, 2020. "The strength of weak leaders: an experiment on social influence and social learning in teams," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 259-293, June.
    12. Foerster, Manuel, 2018. "Finite languages, persuasion bias, and opinion fluctuations," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 46-57.
    13. Angelo Antoci & Guido Ferilli & Paolo Russu & Pier Luigi Sacco, 2020. "Rational populists: the social consequences of shared narratives," Journal of Evolutionary Economics, Springer, vol. 30(2), pages 479-506, April.
    14. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," Papers 2110.10230, arXiv.org.

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    More about this item

    Keywords

    Social networks; Learning; Social influence; Bounded rationality;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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