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Article

Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text

School of Psychology, Shandong Normal University, Jinan 250358, China
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Author to whom correspondence should be addressed.
Academic Editor: Tingshao Zhu
Healthcare 2021, 9(10), 1275; https://doi.org/10.3390/healthcare9101275
Received: 30 July 2021 / Revised: 22 September 2021 / Accepted: 22 September 2021 / Published: 27 September 2021
(This article belongs to the Collection Social Media and Public Health)
(1) Background: in early 2020, COVID-19 broke out. Driven by people’s psychology of conformity, panic, group polarization, etc., various rumors appeared and spread wildly, and the Internet became a hotbed of rumors. (2) Methods: the study selected Weibo as the research media, using topic models, time series analysis, sentiment analysis, and Granger causality testing methods to analyze the social media texts related to COVID-19 rumors. (3) Results: in study 1, we obtained 21 topics related to “COVID-19 rumors” and “outbreak rumors” after conducting topic model analysis on Weibo texts; in study 2, we explored the emotional changes of netizens before and after rumor dispelling information was released and found people’s positive emotions first declined and then rose; in study 3, we also explored the emotional changes of netizens before and after the “Wuhan lockdown” event and found positive sentiment of people in non-Wuhan areas increased, while negative sentiment of people in Wuhan increased; in study 4, we studied the relationship between rumor spread and emotional polarity and found negative sentiment and rumor spread was causally interrelated. (4) Conclusion: These findings could help us to intuitively understand the impact of rumors spread on people’s emotions during the COVID-19 pandemic and help the government take measures to reduce panic. View Full-Text
Keywords: COVID-19; rumors; sentiment analysis; topic model; time series analysis COVID-19; rumors; sentiment analysis; topic model; time series analysis
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MDPI and ACS Style

Wang, P.; Shi, H.; Wu, X.; Jiao, L. Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text. Healthcare 2021, 9, 1275. https://doi.org/10.3390/healthcare9101275

AMA Style

Wang P, Shi H, Wu X, Jiao L. Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text. Healthcare. 2021; 9(10):1275. https://doi.org/10.3390/healthcare9101275

Chicago/Turabian Style

Wang, Peng, Huimin Shi, Xiaojie Wu, and Longzhen Jiao. 2021. "Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text" Healthcare 9, no. 10: 1275. https://doi.org/10.3390/healthcare9101275

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