빅데이터 LDA 토픽 모델링을 활용한 국내 코로나19 대유행 기간 마스크 관련 언론 보도 및 태도 변화 분석. (Korean)

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. [ABSTRACT FROM AUTHOR]

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