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<p>Emergencies not only often cause tragic casualties or huge property loss, but also may lead to severe anxiety. However, few studies have analyzed the factors affecting public anxiety in emergency scenarios. Therefore, this study constructed a research model based on Social Role Theory, Symbolic Interactionism and Terror Management Theory, with the aim of exploring the factors influencing public anxiety from the three aspects of entity characteristics, event characteristics, and event defense. We collected social media posts related to emergencies as well as posters’ information, fine-tuned ChatGLM3-6B using manually labelled datasets to assess anxiety, and used multiple regression analysis to test the theoretical model. The results indicate that both entity characteristics and event characteristics, particularly event harm, significantly influence public anxiety. Attention diversion and intimacy defense can effectively mitigate anxiety. This study introduces a novel approach to analyzing group anxiety during emergencies, advancing the use of big data in this domain, and will offer critical recommendations for monitoring and reducing group anxiety.</p>

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The influencing factors of public anxiety during emergencies: based on big data

  • 期刊论文

  • 发表日期：

    2025年2月19日

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  • Jingfang Liu,
  • Jingxian Cai

摘要

Emergencies not only often cause tragic casualties or huge property loss, but also may lead to severe anxiety. However, few studies have analyzed the factors affecting public anxiety in emergency scenarios. Therefore, this study constructed a research model based on Social Role Theory, Symbolic Interactionism and Terror Management Theory, with the aim of exploring the factors influencing public anxiety from the three aspects of entity characteristics, event characteristics, and event defense. We collected social media posts related to emergencies as well as posters’ information, fine-tuned ChatGLM3-6B using manually labelled datasets to assess anxiety, and used multiple regression analysis to test the theoretical model. The results indicate that both entity characteristics and event characteristics, particularly event harm, significantly influence public anxiety. Attention diversion and intimacy defense can effectively mitigate anxiety. This study introduces a novel approach to analyzing group anxiety during emergencies, advancing the use of big data in this domain, and will offer critical recommendations for monitoring and reducing group anxiety.