The purpose of this study is to analyze the topics of COVID-19 news articles for better obtaining the relationship among and the evolution of news topics, helping to manage the infodemic from a quantified perspective.
To analyze COVID-19 news articles explicitly, this paper proposes a prism architecture. Based on epidemic-related news on China Daily and CNN, this paper identifies the topics of the two news agencies, elucidates the relationship between and amongst these topics, tracks topic changes as the epidemic progresses and presents the results visually and compellingly.
The analysis results show that CNN has a more concentrated distribution of topics than China Daily, with the former focusing on government-related information, and the latter on medical. Besides, the pandemic has had a big impact on CNN and China Daily's reporting preference. The evolution analysis of news topics indicates that the dynamic changes of topics have a strong relationship with the pandemic process.
This paper offers novel perspectives to review the topics of COVID-19 news articles and provide new understandings of news articles during the initial outbreak. The analysis results expand the scope of infodemic-related studies.
