Affective agenda dynamics on social media: interactions of emotional content posted by the public, government, and media during the COVID-19 pandemic

Emotions shared by posters on social media can have a profound impact on individuals and society. This was particularly evident during the COVID-19 pandemic. To examine the types, trends, and dynamics of emotions communicated by the public, government, and media, this study collected 67,689 public posts, 36,740 government posts, and 126,988 media posts on Sina Weibo during the first 6 months of the COVID-19 pandemic. The vector autoregression model and Granger causality analysis were used to measure affective agenda networks and examine affective agenda dynamics. The findings show that the public, government, and media predominantly expressed positive emotions on Sina Weibo. The findings also reveal the significant influence of government emotions on media emotions, which subsequently affects public emotions. This study extends agenda-setting theory by integrating the dimension of emotional contagion. It underscores the potential for government and media to shape public emotions during health crises in order to maintain social order and increase compliance with emergency policies.

Shuhuan Zhou, Xiaokun Yang, Yi Wang, Xia Zheng, Zhian Zhang