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Influencing Opinion Networks: Optimization and Games

Author

Listed:
  • Wout Vos

    (Tilburg University)

  • Peter Borm

    (Tilburg University)

  • Herbert Hamers

    (Tilburg University
    Tilburg University)

Abstract

We consider a model of influence over a network with finite-horizon opinion dynamics. The network consists of agents that update their opinions via a trust structure as in the DeGroot dynamics. The model considers two potential external influencers that have fixed and opposite opinions. They aim to maximally impact the aggregate state of opinions at the end of the finite horizon by targeting with precision one agent in one specific time period. In the case of only one influencer, we characterize optimal targets on the basis of two features: shift and amplification. Also, conditions are provided under which a specific target is optimal: the maximum-amplification target. In the case of two influencers, we focus on the existence and characterization of pure strategy equilibria in the corresponding two-person strategic zero-sum game. Roughly speaking, if the initial opinions are not too much in favour of either influencer, the influencers’ equilibrium behaviour is also driven by the amplification of targets.

Suggested Citation

  • Wout Vos & Peter Borm & Herbert Hamers, 2024. "Influencing Opinion Networks: Optimization and Games," Dynamic Games and Applications, Springer, vol. 14(4), pages 959-980, September.
    • Handle: RePEc:spr:dyngam:v:14:y:2024:i:4:d:10.1007_s13235-023-00543-6
    DOI: 10.1007/s13235-023-00543-6
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    References listed on IDEAS

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    1. Michel Grabisch & Fen Li, 2020. "Anti-conformism in the Threshold Model of Collective Behavior," Dynamic Games and Applications, Springer, vol. 10(2), pages 444-477, June.
    2. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2018. "Strategic Influence in Social Networks," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 29-50, February.
    3. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Comola, Margherita & Rusinowska, Agnieszka & Villeval, Marie Claire, 2024. "Competing for Influence in Networks through Strategic Targeting," IZA Discussion Papers 17315, Institute of Labor Economics (IZA).
    2. Margherita Comola & Agnieszka Rusinowska & Marie Claire Villeval, 2024. "Competing for Influence in Networks Through Strategic Targeting [En compétition pour l'influence dans les réseaux grâce au ciblage stratégique]," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04706311, HAL.

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    More about this item

    Keywords

    Opinion dynamics; Networks; Influence; Targeting; Nash equilibria;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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