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The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.

Multi-period configurational patterns for emotion polarization regulation during major catastrophic emergencies

Zhou, Yuxuan, Zuo, Yipeng, Yang, Yatong·2026·International Journal of Management Science and Engineering Management
DOI 10.1080/17509653.2026.2616016
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Abstract

Major catastrophic emergencies often give rise to a polarization of negative public sentiment within public opinion. Without proper regulation, such polarization can instigate public fear, anger, or even erode government credibility. This paper constructs configurational patterns for official media’s emotion polarization regulation during major emergencies from a causal configuration perspective. Multi-stage nature of major emergencies and the multiple types of public opinion information are considered. Using the China Eastern Airlines MU5735 crash as a study case, trending data throughout the entire cycle of this emergency from Sina Weibo was collected via web crawlers and categorized through topic clustering. This paper defined positive sentiment entropy and constructed sentiment dictionary based on this case. Based on the Yale attitude change model, fifteen potential conditions were specified. To mitigate data redundancy, ensemble models were used to identify key conditions. Multi-period fuzzy-set qualitative comparative analysis (mfsQCA) was then used to identify configurational patterns for moderating collective emotion polarization and deriving decision-oriented implications. This paper offers a configurational perspective on regulating emotion polarization in online public opinion. It also contributes to crisis communication and disaster management by offering methodological insights for moderating public sentiment during emergencies.

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Research works printed but not linked: 3

  1. Berg-Schlosser, D., & Meur, G. (2009). Comparative research design: Case and variable selection. In ResearchGate. https://www.researchgate.net/publication/264120273_Comparative_Research_Design_Case_and_Variable_Selection
  2. Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion. Yale University Press.
  3. Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., & Liu, T.-Y. (2017). LightGBM: A highly efficient gradient boosting decision tree. Advances in Neural Information Processing Systems, 30. https://proceedings.neurips.cc/paper_files/paper/2017/hash/6449f44a102fde848669bdd9eb6b76fa-Abstract.html

Metadata

Authors
Zhou, Y., Zuo, Y., & Yang, Y.
Venue
International Journal of Management Science and Engineering Management
Publisher
Informa UK Limited
Published
2026-01-31
Volume
21
Issue
2
Pages
276-289
ISSN
  • 1750-9653
  • 1750-9661
DOI
10.1080/17509653.2026.2616016
Cited by
0
References
75
Language
en
Funders
  • National Natural Science Foundation of China ([Grant No. 72174134])
  • Major Project of the National Social Science Foundation of China ([Grant No. 22&ZD142])

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