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Bargaining models in opinion dynamics

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  • Zheng, Xi
  • Lu, Xi
  • Chan, Felix T.S.
  • Deng, Yong
  • Wang, Zhen

Abstract

How to reach consensus is the central problem in the research of opinion dynamics. Here we propose the bargaining models under the framework of game theory to involve the non-linearity of opinion dynamics. In this new setup, a dynamic bargaining power is presented to represent the individual difference, which can help to evaluate the profit of changing opinion. Moreover, two types of bargaining models are proposed due to the difference of choosing neighbors. Via numerous simulations, it is unveiled that, with an appropriate environment, both models could lead to the consensus in majority cases, which further enriches the context of opinion dynamics.

Suggested Citation

  • Zheng, Xi & Lu, Xi & Chan, Felix T.S. & Deng, Yong & Wang, Zhen, 2015. "Bargaining models in opinion dynamics," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 162-168.
  • Handle: RePEc:eee:apmaco:v:251:y:2015:i:c:p:162-168
    DOI: 10.1016/j.amc.2014.11.053
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    References listed on IDEAS

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    1. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00982959, HAL.
    2. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    3. Nekovee, M. & Moreno, Y. & Bianconi, G. & Marsili, M., 2007. "Theory of rumour spreading in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 457-470.
    4. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    5. Alessandro Di Mare & Vito Latora, 2007. "Opinion Formation Models Based On Game Theory," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(09), pages 1377-1395.
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    Cited by:

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    2. Kareeva, Yulia & Sedakov, Artem & Zhen, Mengke, 2023. "Influence in social networks with stubborn agents: From competition to bargaining," Applied Mathematics and Computation, Elsevier, vol. 444(C).

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