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Refl ections on the Fat Cat Incident: Characteristics, Laws and Responses to Online Public Opinion in Public Crisis

Hongrui He

Abstract


This study analyzes online public opinion during public crises, focusing on the Fat Cat Incident as a case study. Using Python to
collect Weibo data and machine learning for analysis, we identify a typical crisis evolution process. Findings reveal distinctive interactions in
public opinion regarding heat, emotion, and topics. The paper suggests governance strategies based on crisis stages and multiple stakeholders,
aiming to enhance government crisis management and online public opinion governance.

Keywords


Online public opinion; Fat Cat Incident; Machine learning; Government governance

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References


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DOI: http://dx.doi.org/10.70711/frim.v3i2.6032

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