Abstract
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.
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Data availability
The datasets generated and/or analyzed in the current study are available from the corresponding author on reasonable requests. All datasets can be obtained through the following links:
Weibo-COV 2.0: https://github.com/nghuyong/weibo-cov
Dataset of fine-tuning Chatglm3-6b: https://github.com/xiaocaizier/anxiety-data
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This work is Supported by Shanghai Technical Service Center of Science and Engineering Computing, Shanghai University.
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We received funding from grant 23BGL271 from the National Social Science Fund of China.
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Conceptualization: Jingfang Liu and Jingxian Cai; Methodology: Jingfang Liu and Jingxian Cai; Data curation: Jingxain Cai; Formal analysis and investigation: Jingxian Cai; Resources and Software: Jingxian Cai; Validation: Jingxian Cai; Writing — original draft and Writing — review \& editing: Jingxian Cai. All authors have read and agreed to the published version of the manuscript.
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Liu, J., Cai, J. The influencing factors of public anxiety during emergencies: based on big data. Curr Psychol (2025). https://doi.org/10.1007/s12144-025-07426-6
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DOI: https://doi.org/10.1007/s12144-025-07426-6