The Impact of Shanghai Epidemic, China, 2022 on Public Psychology: A Sentiment Analysis of Microblog Users by Data Mining

Zuqi Wang () and Yanting Qin
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Zuqi Wang: School of Chinese Language and Literature, Jiangsu Normal University, Xuzhou 221116, China
Yanting Qin: School of Liberal Arts, Nanjing University, Nanjing 210023, China

Sustainability, 2022, vol. 14, issue 15, 1-14

Abstract: The Shanghai epidemic (COVID-19) is another large-scale epidemic in China’s central cities in the post-epidemic era from the end of March 2022. It is of great significance to study the public’s attitude towards the Shanghai epidemic to support healthy psychology and a positive attitude. This study used crawler technology to obtain the Weibo data related to the epidemic situation in Shanghai that was published by users. The crawled microblogs were preprocessed, and the BosonNLP sentiment dictionary for attitude classification was selected. The Chinese vocabulary ontology for 21 emotion classifications was also used. The results showed that the general attitude of the public in Shanghai was positive. This fluctuated greatly in the initial stage and gradually increased in the later stage. Through text mining, it is clear that goods and materials, nucleic acid virus testing, and other aspects of the epidemic in Shanghai are concerning for the public. The public attitude in areas that are close to the epidemic center is relatively more negative. The study can provide references for policymakers to fight COVID-19 by improving public attitude and solving urgent matters.

Keywords: Shanghai epidemic situation; text mining; sentiment dictionary; sentiment analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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