Public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage in China : infodemiology study on 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 behavioral compliance. China has experienced the unprecedented epidemic of the coronavirus disease (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 an 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 further explored main content patterns, and chi-square for trend examined how proportions of main content patterns changed by time within the study time frame. Results: The public response to COVID-19 seemed to follow the spread of the disease and government actions but was earlier for Weibo than the government. Online users generally had low engagement with posts relevant to COVID-19 from government agency accounts. The common content patterns identified in personal and government posts included sharing epidemic situations; general knowledge of the new disease; and policies, guidelines, and official actions. However, personal posts were more likely to show empathy to affected people (χ21=13.3, P<.001), attribute blame to other individuals or government (χ21=28.9, P<.001), and express worry about the epidemic (χ21=32.1, P<.001), while government posts were more likely to share instrumental support (χ21=32.5, P<.001) and praise people or organizations (χ21=8.7, P=.003). As the epidemic evolved, sharing situation updates (for trend, χ21=19.7, P<.001) and policies, guidelines, and official actions (for trend, χ21=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 (for trend, χ21=25.3, P<.001) became more frequent in personal posts, corresponding to a slight increase in sharing instrumental support, praising, and empathizing in government posts (for trend, χ21=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 updates 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.