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Dynamics of Uncertain Opinion Formation: An Agent-Based Simulation

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  • Haiming Liang
  • Yucheng Dong
  • Congcong Li

Abstract

Opinion formation describes the dynamics of opinions in a group of interaction agents and is a powerful tool for predicting the evolution and diffusion of the opinions. The existing opinion formation studies assume that the agents express their opinions by using the exact number, i.e., the exact opinions. However, when people express their opinions, sentiments, and support emotions regarding different issues, such as politics, products, and events, they often cannot provide the exact opinions but express uncertain opinions. Furthermore, due to the differences in culture backgrounds and characters of agents, people who encounter uncertain opinions often show different uncertainty tolerances. The goal of this study is to investigate the dynamics of uncertain opinion formation in the framework of bounded confidence. By taking different uncertain opinions and different uncertainty tolerances into account, we use an agent-based simulation to investigate the influences of uncertain opinions in opinion formation from two aspects: the ratios of the agents that express uncertain opinions and the widths of the uncertain opinions, and also provide the explanations of the observations obtained.

Suggested Citation

  • 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.
    • Handle: RePEc:jas:jasssj:2015-104-4
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    References listed on IDEAS

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    1. Wang, Huanjing & Shang, Lihui, 2015. "Opinion dynamics in networks with common-neighbors-based connections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 180-186.
    2. Laurent Salzarulo, 2006. "A Continuous Opinion Dynamics Model Based on the Principle of Meta-Contrast," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-13.
    3. 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.
    4. Guillaume Deffuant & Timoteo Carletti & Sylvie Huet, 2013. "The Leviathan Model: Absolute Dominance, Generalised Distrust, Small Worlds and Other Patterns Emerging from Combining Vanity with Opinion Propagation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(1), pages 1-5.
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    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. Katsuma Mitsutsuji & Susumu Yamakage, 2020. "The dual attitudinal dynamics of public opinion: an agent-based reformulation of L. F. Richardson’s war-moods model," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 439-461, April.

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