Analyzing Antecedent Configurations of Group Emotion Generation in Public Emergencies: A Multi-Factor Coupling Approach

Xiaohan Yan, Yi Liu, Yan Chen, Tiezhong Liu*

*Corresponding author for this work

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Abstract

To enhance emergency management and public opinion governance, improve the accuracy of forecasting group emotional responses, and elucidate the complex pathways of multi-factor coupling in the formation of group emotions, this study constructs a theoretical framework grounded in the social combustion theory. Through web scraping and text sentiment analysis, group emotional tendencies were measured in 40 public emergency cases from the past five years. Using the fuzzy-set qualitative comparative analysis (fsQCA) method, the study explored the coupling, configuration effect, and formation pathways of factors such as “burning substance”, “accelerant”, and “ignition” in the emergence of group emotions. The results reveal significant differences in the generation pathways of positive versus negative group emotion. Inter-group threat as a “burning substance” is more likely to trigger negative group emotion, while “accelerant” plays a pivotal role in shaping and guiding emotional responses. Notably, the government’s response speed is critical for fostering positive emotions, whereas the emergence of rumors significantly contributes to the spread of negative group emotions. Additionally, the occurrence of stimulating events markedly increases the generation of negative group emotions. This study provides an important theoretical foundation and practical insights for the management and regulation of group emotions.

Original languageEnglish
Article number41
JournalBehavioral Sciences
Volume15
Issue number1
DOIs
Publication statusPublished - Jan 2025

Keywords

  • fuzzy-set qualitative comparative analysis
  • generation pathways
  • group emotion
  • multi-factor coupling
  • social combustion theory

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Yan, X., Liu, Y., Chen, Y., & Liu, T. (2025). Analyzing Antecedent Configurations of Group Emotion Generation in Public Emergencies: A Multi-Factor Coupling Approach. Behavioral Sciences, 15(1), Article 41. https://doi.org/10.3390/bs15010041