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Analyzing and predicting network public opinion evolution based on group persuasion force of populism

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  • Fang, Siwei
  • Zhao, Nan
  • Chen, Nan
  • Xiong, Fei
  • Yi, Yunhui

Abstract

The classic individual opinion interaction model, which can effectively explore rule of Individual interaction and trend of public opinion evolution, is frequently used to study evolution of network public opinion, On basis of that, we adopt populism tendency of individual to improve opinion discrepancy threshold and optimize traditional rules of individual opinion interactive. Furthermore, we propose creatively expression of improving group persuasion force based on populism. On this foundation, GPF-NP model is constructed to analyze and predict evolution of opinions of netizens in network populism events. By simulation, we draw conclusion that scale of non-extreme populism play a vital role in evolution of network public opinion. Finally, some proposals are proposed from the simulation result to guide or prevent development of network negative public opinion.

Suggested Citation

  • Fang, Siwei & Zhao, Nan & Chen, Nan & Xiong, Fei & Yi, Yunhui, 2019. "Analyzing and predicting network public opinion evolution based on group persuasion force of populism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 809-824.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:809-824
    DOI: 10.1016/j.physa.2019.04.054
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    References listed on IDEAS

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    Cited by:

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    3. Tao, Chen & Zhong, Guang-Yan & Li, Jiang-Cheng, 2023. "Dynamic correlation and risk resonance among industries of Chinese stock market: New evidence from time–frequency domain and complex network perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).

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