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Analysis of public emotion on flood disasters in southern China in 2020 based on social media data by Mingjun Ma; Qiang Gao; Zishuang Xiao; Xingshuai Hou; Beibei Hu; Lifei Jia; Wenfang Song is a Environmental Science article available to read on EtoBox.

What is Analysis of public emotion on flood disasters in southern China in 2020 based on social media data about?

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 serv

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Author

Mingjun Ma; Qiang Gao; Zishuang Xiao; Xingshuai Hou; Beibei Hu; Lifei Jia; Wenfang Song

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Environmental Science (Physical Sciences)