[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.6109/jkiice.2021.25.5.731

An analysis of the change in media's reports and attitudes about face masks during the COVID-19 pandemic in South Korea: a study using Big Data latent dirichlet allocation (LDA) topic modelling

Suh, Ye-Ryoung (The Department of Security Convergence Science, Chung-Ang University)
Koh, Keumseok Peter (Department of Geography, University of Hong Kong)
Lee, Jaewoo (The Department of Industrial Security, Chung-Ang University)

Publication Information

Journal of the Korea Institute of Information and Communication Engineering / v.25, no.5, 2021 , pp. 731-740 More about this Journal

Abstract

This study applied LDA topic modeling analysis to collect and analyze news media big data related to face masks in the three waves of the COVID-19 pandemic in Korea. The results empirically show that media reports focused on mask production and distribution policies in the first wave and the mandatory mask wearing in the second wave. In contrast, more reports on trivial, gossipy events consist of the media coverage in the second and third waves. The findings imply that Korea's governmental interventions to address the shortage of face masks and to regulate mask wearing were successful relatively in a short time. In contrast, the study also reports that there may be relative less number of science-based news reports like the ones on the effectiveness of face masks or different levels of filter types. This study exemplifies how a big data analysis can be applied to evaluate and enhance public health communication.

Keywords

COVID-19; Mask; News Big data; Topic modeling analysis;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)

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