Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data

As COVID-19 spread around the world, epidemic prevention and control policies have been adopted by many countries. This process has prompted online social platforms to become important channels to enable people to socialize and exchange information. The massive use of social media data mining techniques, to analyze the development online of public opinion during the epidemic, is of great significance in relation to the management of public opinion. This paper presents a study that aims to analyze the developmental course of online public opinion in terms of fine-grained emotions presented during the COVID-19 epidemic in China. It is based on more than 45 million Weibo posts during the period from December 1, 2019 to April 30, 2020. A text emotion extraction method based on a dictionary of emotional ontology has been developed. The results show, for example, that a high emotional effect is observed during holidays, such as New Year. As revealed by Internet users, the outbreak of the COVID-19 epidemic and its rapid spread, over a comparatively short period of time, triggered a sharp rise in the emotion fear. This phenomenon was noted especially in Wuhan and the immediate surrounding areas. Over the initial 2 months, although this fear gradually declined, it remained significantly higher than the more common level of uncertainty that existed during the epidemic's initial developmental era. Simultaneously, in the main city clusters, the response to the COVID-19 epidemic in central cities, was stronger than that in neighboring cities, in terms of the above emotion. The topics of Weibo posts, the corresponding emotions, and the analysis conclusions can provide auxiliary reference materials for the monitoring of network public opinion under similar major public events.

Automated summary

As COVID-19 spread globally, social media became an important channel for people to communicate and exchange information. This study analyzes the development of fine-grained emotions in online public opinion during the COVID-19 epidemic in China, revealing a high emotional effect during holidays and a sharp rise in fear especially in Wuhan and surrounding areas. The study also shows that central cities had stronger reactions to the epidemic compared to neighboring cities.