Analysis of public emotion on flood disasters in southern China in 2020 based on social media data

Mingjun Ma, Qiang Gao, Zishuang Xiao, Xingshuai Hou, Beibei Hu (), Lifei Jia and Wenfang Song
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Mingjun Ma: Tianjin Normal University
Qiang Gao: Tianjin Normal University
Zishuang Xiao: Tianjin Normal University
Xingshuai Hou: Tianjin Normal University
Beibei Hu: Tianjin Normal University
Lifei Jia: Tianjin Normal University
Wenfang Song: Tianjin Normal University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 118, issue 2, No 7, 1013-1033

Abstract: Abstract The exploding popularity of social networks provides a new opportunity to study disasters and public emotion. Among the social networks, Weibo is one of the largest microblogging services in China. Taking Guangdong and Guangxi in the south of China as a case, Web Scraper was used to obtain Weibo texts related to floods in 2020. The spatial distribution of floods was analyzed using Kernel Density Estimation. Public emotion was analyzed using Natural Language Processing tools. The association between floods and public emotion was explored through correlation analysis methods. The results indicated that: (1) Weibo texts could be utilized as effective data to identify urban waterlogging risk in Guangdong and Guangxi. (2) The waterlogging was mainly distributed in the southern part of Guangdong and Guangxi, especially in the provincial capitals and coastal cities. (3) Public emotion was predominantly negative, especially during periods of heavy precipitation. (4) There was a strong correlation between public emotion and floods in spatial–temporal variation. The degree of negative public emotion was significantly influenced by the number of waterlogging points. The presented results serve as the preliminary data for future planning and designing of emergency management. Graphical abstract

Keywords: Flood; Weibo texts; Public emotion; Guangdong; Guangxi (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06033-7

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