Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example

Bowen Zhang, Jinping Lin, Man Luo, Changxian Zeng, Jiajia Feng, Meiqi Zhou and Fuying Deng ()
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Bowen Zhang: School of Earth Sciences, Yunnan University, Kunming 650000, China
Jinping Lin: School of Earth Sciences, Yunnan University, Kunming 650000, China
Man Luo: School of Earth Sciences, Yunnan University, Kunming 650000, China
Changxian Zeng: Faculty of Science, Dalian University for Nationalities, Dalian 116000, China
Jiajia Feng: School of Earth Sciences, Yunnan University, Kunming 650000, China
Meiqi Zhou: School of Tourism and Geographical Sciences, Yunnan Normal University, Kunming 650000, China
Fuying Deng: School of Earth Sciences, Yunnan University, Kunming 650000, China

IJERPH, 2022, vol. 19, issue 19, 1-20

Abstract: The occurrence of major health events can have a significant impact on public mood and mental health. In this study, we selected Shanghai during the 2019 novel coronavirus pandemic as a case study and Weibo texts as the data source. The ERNIE pre-training model was used to classify the text data into five emotional categories: gratitude, confidence, sadness, anger, and no emotion. The changes in public sentiment and potential influencing factors were analyzed with the emotional sequence diagram method. We also examined the causal relationship between the epidemic and public sentiment, as well as positive and negative emotions. The study found: (1) public sentiment during the epidemic was primarily affected by public behavior, government behavior, and the severity of the epidemic. (2) From the perspective of time series changes, the changes in public emotions during the epidemic were divided into emotional fermentation, emotional climax, and emotional chaos periods. (3) There was a clear causal relationship between the epidemic and the changes in public emotions, and the impact on negative emotions was greater than that of positive emotions. Additionally, positive emotions had a certain inhibitory effect on negative emotions.

Keywords: ERNIE pre-training model; emotions; Coupla entropy; COVID-19; Shanghai (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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