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An agent-based model of opinion dynamics with attitude-hiding behaviors

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  • Zhu, Jiefan
  • Yao, Yiping
  • Tang, Wenjie
  • Zhang, Haoming

Abstract

People might remain silent or give an opinion that is inconsistent with their private convictions when there is a divergence between their own views and the opinion voiced in their surrounding environment. This behavior suppresses the spread of weak opinions and affects the evolution of public opinion. Current opinion dynamics models do not fully consider this practice of attitude hiding. Thus, they are unable to reflect the phenomenon caused by individuals keeping silent. To solve this problem, based on online social networks, we propose an opinion dynamics model considering attitude-hiding behavior. Individuals perceive opinion climate based on feedbacks of expressions in history and use it to assess popularity of their newly opinions. They may keep silent and adjust expressible opinions to show obedience to the opinion climate. Experimental results and comparison with two related models indicate that our model can simulate the evolution of multiple public opinions associated with reality. Consequently, it provides a clearer explanation of the law and cause of the evolution of public opinion from the viewpoint of individuals’ behaviors.

Suggested Citation

  • Zhu, Jiefan & Yao, Yiping & Tang, Wenjie & Zhang, Haoming, 2022. "An agent-based model of opinion dynamics with attitude-hiding behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
  • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122004459
    DOI: 10.1016/j.physa.2022.127662
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    References listed on IDEAS

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    1. 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.
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    4. Luo, Yun & Li, Yuke & Sun, Chudi & Cheng, Chun, 2022. "Adapted Deffuant–Weisbuch model with implicit and explicit opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    5. 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.
    6. Hossein Noorazar & Kevin R. Vixie & Arghavan Talebanpour & Yunfeng Hu, 2020. "From classical to modern opinion dynamics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(07), pages 1-60, July.
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    Cited by:

    1. Zhang, Yaozeng & Ma, Jing & Fang, Fanshu, 2024. "How social bots can influence public opinion more effectively: Right connection strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).

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