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Public Opinion Polarization by Individual Revenue from the Social Preference Theory

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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)

  • Peihua Fu

    (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)

  • Chonghuan Xu

    (School of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China)

  • 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

Social conflicts occur frequently during the social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making behaviors driven by the revenue. Secondly, the revenue function is used to judge the exit rules of nodes in a network, and then a dynamic network of spreading public opinion with the node (individual) exit mechanism is built based on a BA scale-free network. Subsequently, the influences of different social preferences, as well as individual revenue on the effect of public opinion polarization, are analyzed through simulation experiments. The simulation results show that (1) Different social preferences demonstrate different influences on the evolution of public opinions, (2) Individuals tend to interact with ones with different preferences, (3) The network with a single preference or a high aggregation is more likely to form public opinion polarization. Finally, the practicability and effectiveness of the proposed model are verified by a real case.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:3:p:946-:d:316074
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    References listed on IDEAS

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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. 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.
    3. 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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