Intermedia Agenda Setting amid the Pandemic: A Computational Analysis of China's Online News.

ABSTRACT

Based on Intermedia Agenda Setting (IAS), the current study examines how official media and semi-privatized commercial media on the Weibo platform covered the COVID-19 pandemic in China. Both supervised machine learning and time series analysis were employed to analyze 350,059 Weibo posts released by 3,883 news sources between December 2019 and April 2020. Our results indicated that, in this nonwestern state-regulated China media environment, official and semi-privatized commercial media had a significant reciprocal relationship in news coverage. Both of them focused on "treatment on patients," "work resumption," and "propaganda and mobilization." Importantly, this paper sheds light on the value of the fine-grained level of agenda in IAS research. Using a fine-grained analysis, we separately investigated the effects of official and semi-privatized commercial media on predicting the pandemic prevalence, referring to the number of confirmed cases reported in real time. Implications and future directions were further discussed.