Learning public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage in China: an analysis of social media data

ABSTRACT

BACKGROUND: Effective risk communication about the outbreak of a newly emerging infectious disease in the early stage is critical for managing public anxiety and promoting behavioural compliance. China has experienced the unprecedented epidemic of coronavirus disease 2019 (COVID-19) in an era when social media has fundamentally transformed information production and consumption patterns. OBJECTIVE: This study examined public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage based on analysis of data from Sina Weibo, a major social media platform in China. METHODS: Weibo data relevant to COVID-19 from December 1, 2019 to January 31, 2020 were retrieved. Engagement data (Likes, Comments, Shares and Followers) of posts from government agency accounts were extracted to evaluate public engagement with government posts online. Content analyses were conducted for a random subset of 644 posts from personal accounts of individuals, and 273 posts from 10 relatively more active government agency accounts and the National Health Commission of China to identify major thematic contents in online discussions. Latent class analysis (LCA) was employed to further explore main content patterns while Chi-square for trend examined how proportions of main content patterns changed by time within the study timeframe. RESULTS: Public response to COVID-19 seemed to follow the spread of the disease and government actions but was earlier on Weibo than the government. Online users generally had low engagement with posts relevant COVID-19 from government agency accounts. The common content patterns identified in personal and government posts included sharing epidemic situation, general knowledge of the new disease, and policies, guidelines and official actions. However, personal posts more likely showed empathy to affected people (chi-square=13.3, P<.001), attributed blame to other individuals or government (chi-square=28.9, P<.001), and expressed worry about the epidemic (chi-square=32.1, P<.001) while government posts more likely shared instrumental support (chi-square=32.5, P<.001) and praised people or organizations (chi-square=8.7, P=.003). As the epidemic evolved, sharing situation update (chi-square for trend=19.7, P<.001), and policies, guidelines and official actions (chi-square for trend=15.3, P<.001) became less frequent in personal posts but remained stable or increased significantly in government posts. Moreover, as the epidemic evolved, showing empathy and attributing blame (chi-square for trend=25.3, P<.001) became more frequent in personal posts, corresponding to a slight increase in sharing instrumental support, praising and empathy in government posts (chi-square for trend=9.0, P=.003). CONCLUSIONS: The government should closely monitor social media data to improve the timing of communications about an epidemic. As the epidemic evolves, merely sharing situation update and policies may be insufficient to capture public interest in the messages. The government may adopt a more empathic communication style as more people are affected by the disease to address public concerns. CLINICALTRIAL Not applicable.