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Dynamics of Public Opinion: Diverse Media and Audiences’ Choices

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  • Zhongtian Chen
  • Hanlin Lan

Abstract

Studies on the fundamental role of diverse media in the evolution of public opinion can protect us from the spreading of brainwashing, extremism, and terrorism. Many fear the information cocoon may result in polarization of the public opinion. Hence, in this work, we investigate how audiences' choices among diverse media might influence public opinion. Specifically, we aim to figure out how peoples' horizons (i.e., range of available media) and quantity, as well as the distribution of media, may shape the space of public opinion. We propose a novel model of opinion dynamics that considers different influences and horizons for every individual, and we carry out simulations using a real-world social network. Numerical simulations show that diversity in media can provide more choices to the people, although individuals only choose media within the bounds of their horizons, extreme opinions are more diluted, and no opinion polarizations emerge. Furthermore, we find that the distribution of media's opinions can effectively influence the space for public opinion, but when the number of media grows to a certain level, its effect will reach a limitation. Finally, we show that the effect of campaigns for consciousness or education can be improved by constructing the opinion of media, which can provide a basis for the policy maker in the new media age.

Suggested Citation

  • Zhongtian Chen & Hanlin Lan, 2021. "Dynamics of Public Opinion: Diverse Media and Audiences’ Choices," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(2), pages 1-8.
  • Handle: RePEc:jas:jasssj:2020-131-2
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    References listed on IDEAS

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    1. 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.
    2. Fan, Kangqi & Pedrycz, Witold, 2015. "Emergence and spread of extremist opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 87-97.
    3. 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.
    4. Haibo Hu & Jonathan J. H. Zhu, 2017. "Social networks, mass media and public opinions," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 393-411, July.
    5. Liu, Wenjin & Li, Tao & Cheng, Xinming & Xu, Hao & Liu, Xiongding, 2019. "Spreading dynamics of a cyber violence model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
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    Cited by:

    1. Ding, Haixin & Xie, Li, 2024. "The applicability of positive information in negative opinion management: An attitude-laden communication perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).

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