Abstract
The spread of COVID-19 pandemic and the participation of Internet information are continually changing the public’s positive emotions and risk perception. However, relatively little is known about the underlying mechanism of how the COVID-19 dynamic situation affects the public’s risk perception and emotions. This study uses the social risk amplification framework (SRAF) as the theoretical basis to collect and analyze Hubei Province data from January 20 to April 8, 2020, including the number of newly diagnosed people per day, the proportion of positive emotional posts in Weibo, and the Baidu search index (BSI). The autoregressive integrated moving average (ARIMAbased time-series prediction model is used to analyze the dynamic evolution laws and fluctuation trends of Weibo positive emotions and risk perception during the development of the pandemic. The conclusion of the study is that positive emotions are negatively correlated with risk perception, the severity of the pandemic situation is negatively correlated with positive emotions, and the severity of the pandemic situation is positively correlated with risk perception. The public has a keen response to the dynamics of the pandemic situation and the government’s decision-making behavior, which is manifested by the significant changes in positive emotions and risk perception in the corresponding period. The research results can provide a reference for government departments to guide the public to establish an objective risk perception and maintain positive and stable emotions in similar catastrophes.
Highlights
COVID-19 is still spreading around the world
According to the research results, we believe that the proportion of positive emotions in Weibo is negatively correlated with the Baidu Search Index (BSI), which means that when the public’s emotions have a negative tendency, risk perception will be greatly increased
Research on employees in Shanghai, China, shows that employees who are more sensitive to the COVID-19 risks show higher negative emotions and work stress [57]; the severity of the pandemic is negatively correlated with the proportion of positive emotions, which means as the severity of the pandemic continues to increase, the people’s emotions become negative, and the proportion of positive emotions will show a downward trend. is is not surprising at all. e results of a survey of more than 50,000 people proved our judgment
Summary
COVID-19 is still spreading around the world. Almost all countries and regions have adopted different forms and different levels of response measures, whether at the government, organization, or individual level [1]. Irrational activities during the pandemic are not conducive to effective selfprotection by the public and have a great negative impact on the antipandemic activities of the entire society To this end, it is important to keep abreast of the public opinion of the COVID-19 pandemic and accurately assess the dynamic evolution of positive emotional and risk perception in crises. Similar to Twitter, Sina Weibo is the most widely used social networking platform in China and has become a place for gathering information [16] It contains a large number of news hotspots and the emotional tendency of netizens and plays an important role in the spread of emergencies and other emergencies [17]. In the context of the COVID-19 pandemic and community lockdown, it is of great significance to study the relationship and dynamic trends among the public’ positive emotions, risk perception, and severity of the pandemic in Hubei Province. e data collection and data analysis methods of this study are novel and reasonable, and the results are quite convincing, which can provide references for similar disaster research. is research can scientifically and effectively analyze the positive emotions and risk perceptions of the public in Hubei Province in response to COVID-19 and provide theoretical basis and suggestions for government departments to guide the public to establish correct risk perceptions and maintain stable emotions during disasters
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