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Research on emotional tendency of earthquake disaster based on E-Trans model: take the topic of “Sichuan Earthquake” on microblog as an example

Author

Listed:
  • Qinglu Yuan

    (Institute of Disaster Prevention)

  • Shujuan Wang

    (Institute of Disaster Prevention)

  • Nan Li

    (Institute of Disaster Prevention)

Abstract

With the rapid development of network technology, research on the emotional tendencies of online disasters has increasingly played a significant role in responding to disaster public opinion events. This paper collected data from microblogs and selects three relatively large earthquakes that occurred in Sichuan in 2022 as research samples, namely the Lushan earthquake that occurred on June 1, the Malkang earthquake that occurred on June 10, and the Luding earthquake that occurred on September 5. By calling the E-Trans emotional analysis model, the emotional tendency values were obtained. Using Python language and a time–frequency of 15 min, the original content posted by microblog users within 24 h after the earthquake was analyzed for emotional tendencies, and research conclusions were drawn on the characteristics of emotional tendencies in earthquake disasters and related factors. The results show that the emotional tendencies of the three earthquakes conform to the “Three·Three” emotional tendency model for disasters, and the emotional tendency values in the three periods show a significant marginal diminishing effect. Changes in emotional tendencies during earthquake disasters are mainly related to the magnitude of the earthquake, the number of aftershocks, issues that the public is more concerned about on microblogs, and earthquake prevention and mitigation department microblog promotions. This study can provide a reference for post-disaster emergency response and network public opinion guidance for earthquake prevention and mitigation.

Suggested Citation

  • Qinglu Yuan & Shujuan Wang & Nan Li, 2024. "Research on emotional tendency of earthquake disaster based on E-Trans model: take the topic of “Sichuan Earthquake” on microblog as an example," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(6), pages 5057-5074, April.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:6:d:10.1007_s11069-024-06421-7
    DOI: 10.1007/s11069-024-06421-7
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    References listed on IDEAS

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    1. Hua Bai & Guang Yu, 2016. "A Weibo-based approach to disaster informatics: incidents monitor in post-disaster situation via Weibo text negative sentiment analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1177-1196, September.
    2. Ying Ji & Huanhuan Li & Huijie Zhang, 2022. "Risk-Averse Two-Stage Stochastic Minimum Cost Consensus Models with Asymmetric Adjustment Cost," Group Decision and Negotiation, Springer, vol. 31(2), pages 261-291, April.
    3. Rositsa T. Ilieva & Timon McPhearson, 2018. "Social-media data for urban sustainability," Nature Sustainability, Nature, vol. 1(10), pages 553-565, October.
    4. Shivaji Alaparthi & Manit Mishra, 2021. "BERT: a sentiment analysis odyssey," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 118-126, June.
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