A new perspective to understand public response to the Typhoon Doksuri from coastal and inland regions
- PMID: 39263054
- PMCID: PMC11388730
- DOI: 10.1016/j.heliyon.2024.e36862
A new perspective to understand public response to the Typhoon Doksuri from coastal and inland regions
Abstract
Massive amounts of data from social media possess the potential to rapidly identify the primary issues of concern in emergency disaster management. In summer 2023, Super Typhoon Doksuri which was an exceptionally special typhoon disaster that caused severe damage to China's coastal areas and disastrous impacts in inland regions, particularly triggered the most severe rainstorm in Beijing area in over a century. To enhance typhoon hazard reduction in both coastal and interior locations, it is crucial to examine public response to these events. This study uses microblog text data from July 27 to August 3 of 2023 to map the public response to Typhoon Doksuri. The Support Vector Machine (SVM) algorithm was used to classify the microblog text in combination with the typhoon path to analyze the spatial and temporal variations of the emotions of the affected individuals. The relationship between changes in public opinion, the distribution of topics, and the major disasters triggered by the residual circulation of Typhoon Doksuri in the Beijing-Tianjin-Hebei region is discussed. The Mentougou mega-storm in Beijing area that occurred in July 2023 is a typical case. The findings demonstrate that during the typhoon event, the focus of public attention changed with the movement of the typhoon path, and various public opinion topics exhibited temporal synchronization. Public sentiment indicates that the overall supportive sentiment is higher than is fearful sentiment. Based on this, it is crucial to strengthen the Beijing-Tianjin-Hebei cooperative emergency response, and response measures were proposed related to urban flood control and drainage construction, public awareness, backward areas, secondary disasters, resident relocation, and social media technology.
Keywords: Data mining; Disaster prevention and mitigation; Public opinion; Typhoon disaster.
© 2024 The Authors.
Conflict of interest statement
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Juanle Wang reports financial support was provided by the National Key R&D Program of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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References
-
- Zheng S. Characteristics of spatial and temporal distribution of tropical cyclones making landfall in China in the past 23 years and their impacts. China Water Transport. 2023;23(11):55–57.
-
- China's ocean disaster monitoring and early warning technology laboratory. China's Ocean Disaster Report. 2022 [M])
-
- MEM (Ministry of Emergency Management of the People’s Republic of China) Releases national natural disasters for july 2023. [EB/OL] 2023 https://www.mem.gov.cn/xw/yjglbgzdt/202308/t20230804_458461.shtml
-
- Jin C., Wu W.Y., Chen B.R., et al. Analysis and comparative study of the evolution of public opinion on social media during typhoon for different user groups. Journal of Geo-information Science. 2021;23(12):2174–2186. doi: 10.12082/dqxxkx.2021.210065. - DOI
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