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Impact of information on public opinion reversal—An agent based model

Author

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  • Zhu, Hou
  • Hu, Bin

Abstract

Reversal of public opinion is an important phenomenon of opinion evolution besides consensus and polarization. Information released by someone often boosts others to change their opinion because the basis of their opinion decision is enriched. As an important external force, information may change the trend of opinion evolution, even reverse the state of public opinion. In order to explore the impact of information on public opinion evolution in macro level, especially reversal, this paper models information as a variable and embeds it into bounded confidence model based on agent based simulation, and then validates the model based on an empirical case. Information strength, time of releasing information and different types of information countermeasure are analyzed through a large number of simulation experiments to find out principles of public opinion reversal. The result shows that information released during the event can change and even reverse the orientation of public opinion, but different releasing mode will produce different result of public opinion evolution.

Suggested Citation

  • Zhu, Hou & Hu, Bin, 2018. "Impact of information on public opinion reversal—An agent based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 578-587.
  • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:578-587
    DOI: 10.1016/j.physa.2018.08.085
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    References listed on IDEAS

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    Cited by:

    1. Gong, Hao & Guo, Chunxiang & Liu, Yu, 2021. "Measuring network rationality and simulating information diffusion based on network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    2. 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.
    3. Shan Gao & Ye Zhang & Wenhui Liu, 2021. "How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?," IJERPH, MDPI, vol. 18(15), pages 1-14, July.
    4. Dong, Xuefan & Lian, Ying, 2021. "A review of social media-based public opinion analyses: Challenges and recommendations," Technology in Society, Elsevier, vol. 67(C).

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