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Opinion evolution and rare events in an open community

Author

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  • Ye, Yusong
  • Yang, Zhuoqin
  • Zhang, Zili

Abstract

There are many multi-stable phenomena in society. To explain these multi-stable phenomena, we have studied opinion evolution in an open community. We focus on probability of transition (or the mean transition time) that the system transfer from one state to another. We suggest a bistable model to provide an interpretation of these phenomena. The quasi-potential method that we used is the most important method to calculate the transition time and it can be used to determine the whole probability density. We study the condition of bistability and then discuss rare events in a multi-stable system. In our model, we find that two parameters, “temperature” and “persuading intensity,” influence the behavior of the system; a suitable “persuading intensity” and low “temperature” make the system more stable. This means that the transition rarely happens. The asymmetric phenomenon caused by “public-opinion” is also discussed.

Suggested Citation

  • Ye, Yusong & Yang, Zhuoqin & Zhang, Zili, 2016. "Opinion evolution and rare events in an open community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1178-1188.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:1178-1188
    DOI: 10.1016/j.physa.2016.06.084
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    References listed on IDEAS

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    1. Cheng Lv & Xiaoguang Li & Fangting Li & Tiejun Li, 2014. "Constructing the Energy Landscape for Genetic Switching System Driven by Intrinsic Noise," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
    2. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    3. Kaizoji, Taisei, 2000. "Speculative bubbles and crashes in stock markets: an interacting-agent model of speculative activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 493-506.
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