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Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity

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  • Tinggui Chen

    (School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China
    School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Qianqian Li

    (School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Jianjun Yang

    (Department of Computer Science and Information Systems, University of North Georgia, Oakwood, GA 30566, USA)

  • Guodong Cong

    (School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China)

  • Gongfa Li

    (Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

Abstract

Nowadays, hot issues are likely become bipolar or multipolar after heated discussion on the Internet. This article is focused on the study of the polarization phenomenon and establishes a public opinion polarization model with the considerations of individual heterogeneity and dynamic conformity. At first, this article introduces the dynamic changing function of an individual’s conformity tendency to other’s attitudes in the interaction process. It further defines the influential weight between different interactive individuals, and expands the interactive individual from complete homogeneity to initial attitude heterogeneity, and finally, conformity heterogeneity. Then, through simulation experiments, we find that the degree of changing in individual attitude is limited. That is, it is difficult for the individuals who have one directional attitude at the initial time to change into another opposite attitude through interaction. In addition, individuals with low conformity within a certain threshold are more likely to form polarization. Finally, the rationality and effectiveness of the proposed model are verified by the typical case “Mimeng Event”.

Suggested Citation

  • Tinggui Chen & Qianqian Li & Jianjun Yang & Guodong Cong & Gongfa Li, 2019. "Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity," Mathematics, MDPI, vol. 7(10), pages 1-33, October.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:10:p:917-:d:272981
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    Cited by:

    1. Peihua Fu & Bailu Jing & Tinggui Chen & Jianjun Yang & Guodong Cong, 2020. "Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions," IJERPH, MDPI, vol. 17(18), pages 1-29, September.
    2. Wu, Yue & Li, Linjiao & Yu, Qiannan & Gan, Jiaxin & Zhang, Yi, 2023. "Strategies for reducing polarization in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    3. Tinggui Chen & Qianqian Li & Peihua Fu & Jianjun Yang & Chonghuan Xu & Guodong Cong & Gongfa Li, 2020. "Public Opinion Polarization by Individual Revenue from the Social Preference Theory," IJERPH, MDPI, vol. 17(3), pages 1-29, February.
    4. Ziyuan Liu & Zhi Li & Weiming Chen & Yunpu Zhao & Hanxun Yue & Zhenzhen Wu, 2020. "Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune–Ant Colony Algorithm," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    5. Tinggui Chen & Yulong Wang & Jianjun Yang & Guodong Cong, 2021. "Modeling Multidimensional Public Opinion Polarization Process under the Context of Derived Topics," IJERPH, MDPI, vol. 18(2), pages 1-34, January.

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