@article{wang_shi_wu_jiao_2021, 
  title={Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text}, 
  volume={9}, 
  DOI={10.3390/healthcare9101275}, 
  abstractNote={<jats:p>(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.</jats:p>}, 
  number={10}, 
  publisher={MDPI AG}, 
  author={Wang, Peng and Shi, Huimin and Wu, Xiaojie and Jiao, Longzhen}, 
  year={2021}, 
  month={Sep}
  }