Microblog data analysis of emotional reactions to COVID-19 in China

• Published in: Journal of psychosomatic research 2022-10, Vol.161, p.110976-110976, Article 110976
• Main Authors: Jin, Yuchang, Yan, Aoxue, Sun, Tengwei, Zheng, Peixuan, An, Junxiu
• Format: Article
• Language: English
• Subjects: Basic emotions; China - epidemiology; COVID-19; Data Analysis; Data mining; Humans; Pandemics; Sentiment analysis technology; Sina microblogs; Social Media
• ISSN: 0022-3999; 1879-1360
• DOI: 10.1016/j.jpsychores.2022.110976

To explore the emotional attitudes of microblog users in the different COVID-19 stages in China, this study used data mining and machine-learning methods to crawl 112,537 Sina COVID-19- related microblogs and conduct sentiment and group difference analyses. It was found that: (1) the microblog users' emotions shifted from negative to positive from the second COVID-19 pandemic phase; (2) there were no significant differences in the microblog users' emotions in the different regions; (3) males were more optimistic than females in the early stages of the pandemic; however, females were more optimistic than males in the last three stages; and (4) females posted more microblogs and expressed more sadness and fear while males expressed more anger and disgust. This research captured online information in real-time, with the results providing a reference for future research into public opinion and emotional reactions to crises. •The microblog users' emotions shifted from negative to positive from the second stage of COVID-19 in China.•There were no obvious differences in the microblog users' emotions in different regions.•Males were more optimistic than females in the early stages of the pandemic.•Females were more optimistic than males in the last three stages.