Topic Models to Analyze Disaster-Related Newspaper Articles: Focusing on COVID-19

Abstract

Major media outlets have run many articles on the COVID-19 pandemic. Since the public suffers cognitive and emotional effects related to COVID-19 from such reports, we analyzed and reviewed the topics of news reports. We searched newspaper articles with the term ‘COVID-19’ term in four Korean daily newspapers from January 20, 2020, when the first patient in Korea was found, to June 15, 2020. Topic modeling analysis was conducted through text mining using R. Five themes were found: “Changes in people’s everyday life,” “Socio-economic shock,” “Trends in infection,” “Role of the government and business,” and “Increased psychological anxiety,” which all showed sharp increases in articles from mid-February to early March and then decreased. Despite the increased psychological anxiety people suffered from the COVID-19 pandemic, this topic showed the fewest articles. “Changes in people’s everyday life” showed the most, focusing attention on stimulating lifestyle articles of general interest. Since the COVID-19 pandemic can lead to mental health problems due to severe changes and isolation in everyday life, a comprehensive response to the news focusing on the impact on the mental health of the population around the world should be made.