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Neighborhood models of minority opinion spreading

Author

Listed:
  • C. J. Tessone
  • R. Toral
Abstract
We introduce neighborhood models that account for local spatial effects in Galam's model [1] of minority opinion spreading. This model describes the spread of a minority opinion, incorporating absic mechanisms of social inertia, resulting in democratic rejection of social reforms initially favored by a majority. For systems with a number of agents N, the time to reach consensus is shown to scale with log(N) in Galam's model, while it grows linearly with N in the new neighborhood models. The threshold value of the initial concentration of minority supporters for the defeat of the initial majority, which is independent of N in Galam's model, goes to zero with growing number of agents in the neighborhood models. We show that this is a consequence of the existence of a critical size for the growth of a local domain of majority supporters

Suggested Citation

  • C. J. Tessone & R. Toral, 2004. "Neighborhood models of minority opinion spreading," Computing in Economics and Finance 2004 206, Society for Computational Economics.
    • Handle: RePEc:sce:scecf4:206
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    Citations

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    Cited by:

    1. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    2. Fang Wu & Bernardo A. Huberman, 2004. "Social Structure and Opinion Formation," Computational Economics 0407002, University Library of Munich, Germany.
    3. Galam, Serge, 2010. "Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3619-3631.
    4. Wang, Shaoli & Rong, Libin & Wu, Jianhong, 2016. "Bistability and multistability in opinion dynamics models," Applied Mathematics and Computation, Elsevier, vol. 289(C), pages 388-395.
    5. Serge Galam, 2007. "From 2000 Bush–Gore to 2006 Italian elections: voting at fifty-fifty and the contrarian effect," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(4), pages 579-589, August.
    6. Galam, Serge, 2011. "Collective beliefs versus individual inflexibility: The unavoidable biases of a public debate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3036-3054.
    7. Mehrdad Agha Mohammad Ali Kermani & Reza Ghesmati & Masoud Jalayer, 2018. "Opinion-Aware Influence Maximization: How To Maximize A Favorite Opinion In A Social Network?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-27, September.
    8. Balankin, Alexander S. & Martínez Cruz, Miguel Ángel & Martínez, Alfredo Trejo, 2011. "Effect of initial concentration and spatial heterogeneity of active agent distribution on opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3876-3887.
    9. Fang, Siwei & Zhao, Nan & Chen, Nan & Xiong, Fei & Yi, Yunhui, 2019. "Analyzing and predicting network public opinion evolution based on group persuasion force of populism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 809-824.
    10. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    11. Yaofeng Zhang & Renbin Xiao, 2015. "Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-15, August.

    More about this item

    Keywords

    Agent-based Models; Dynamics of social systems.;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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