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Opinion Formation by Informed Agents

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Abstract

Opinion formation and innovation diffusion have gained lots of attention in the last decade due to its application in social and political science. Control of the diffusion process usually takes place using the most influential people in the society, called opinion leaders or key players. But the opinion leaders can hardly be accessed or hired for spreading the desired opinion or information. This is where informed agents can play a key role. Informed agents are common people, not distinguishable from the other members of the society that act in coordination. In this paper we show that informed agents are able to gradually shift the public opinion toward a desired goal through microscopic interactions. In order to do so they pretend to have an opinion similar to others, but while interacting with them, gradually and intentionally change their opinion toward the desired direction. In this paper a computational model for opinion formation by the informed agents based on the bounded confidence model is proposed. The effects of different parameter settings including population size of the informed agents, their characteristics, and network structure, are investigated. The results show that social and open-minded informed agents are more efficient than selfish or closed-minded agents in control of the public opinion.

Suggested Citation

  • Mohammad Afshar & Masoud Asadpour, 2010. "Opinion Formation by Informed Agents," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 1-5.
    • Handle: RePEc:jas:jasssj:2010-28-2
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    Citations

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    Cited by:

    1. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    2. Yan, Fuhan & Li, Zhaofeng & Jiang, Yichuan, 2016. "Controllable uncertain opinion diffusion under confidence bound and unpredicted diffusion probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 85-100.
    3. 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.
    4. Alireza Mansouri & Fattaneh Taghiyareh, 2020. "Phase Transition in the Social Impact Model of Opinion Formation in Scale-Free Networks: The Social Power Effect," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(2), pages 1-3.
    5. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.
    6. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2020. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks," Mathematics, MDPI, vol. 8(12), pages 1-25, December.
    7. David Anzola & Peter Barbrook-Johnson & Juan I. Cano, 2017. "Self-organization and social science," Computational and Mathematical Organization Theory, Springer, vol. 23(2), pages 221-257, June.
    8. Carlos Andres Devia & Giulia Giordano, 2023. "Classification-Based Opinion Formation Model Embedding Agents’ Psychological Traits," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(3), pages 1-1.
    9. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    10. Ghezelbash, Ehsan & Yazdanpanah, Mohammad Javad & Asadpour, Masoud, 2019. "Polarization in cooperative networks through optimal placement of informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. Ricardo Almeida & Agnieszka B. Malinowska & Tatiana Odzijewicz, 2019. "Optimal Leader–Follower Control for the Fractional Opinion Formation Model," Journal of Optimization Theory and Applications, Springer, vol. 182(3), pages 1171-1185, September.
    12. Fan, Kangqi & Pedrycz, Witold, 2017. "Evolution of public opinions in closed societies influenced by broadcast media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 53-66.
    13. Francisco J. León-Medina & Jordi Tena-Sánchez & Francisco J. Miguel, 2020. "Fakers becoming believers: how opinion dynamics are shaped by preference falsification, impression management and coherence heuristics," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 385-412, April.
    14. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    15. Haiming Liang & Yucheng Dong & Congcong Li, 2016. "Dynamics of Uncertain Opinion Formation: An Agent-Based Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-1.

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