Text mining of the media coverage of major public health emergencies: a case study of COVID-19

ObjectiveBased on the text analysis of COVID-19 media report, text mining was used to probe the trend of major public health emergencies and response of the government and social subjects in China.

MethodsUsing the topic model method, we focused on the quantity of news report, topic content, development trend, and emotional tendency, to present the characteristics of media report on China's public health emergency, and the response mechanism of the Chinese government and the whole society.

ResultsThe media report and news commentary of COVID-19 showed a consistent trend with the epidemic progress. The governmental response was the main target of media report, while social power, medical progress and other categories also attracted some attention. The development trend of different topics was characterized by continual or periodic variation due to their different attributes.

ConclusionThe topic model method comprehensively demonstrates the development and response process of the COVID-19 epidemic. The model may provide a new perspective to improve the national public emergency management system.