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Article

Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data

1
Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul 03063, Korea
2
Department of Interaction Science, Sungkyunkwan University, Seoul 03063, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Tae-Hyoung (Tommy) Gim, Chang-Yu Hong and Sven Bremberg
Int. J. Environ. Res. Public Health 2021, 18(12), 6432; https://doi.org/10.3390/ijerph18126432
Received: 21 April 2021 / Revised: 10 June 2021 / Accepted: 11 June 2021 / Published: 14 June 2021
(This article belongs to the Special Issue Urban and Public Policy against COVID-19)
Media plays an important role in the acquisition of health information worldwide. This was particularly evident in the face of the COVID-19 epidemic. Relatedly, it is practical and desirable for people to wear masks for health, fashion, and religious regions. However, depending on cultural differences, people naturally accept wearing a mask, or they look upon it negatively. In 2020, the COVID-19 pandemic led to widespread mask-wearing mandates worldwide. In the case of COVID-19, wearing a mask is strongly recommended, so by analyzing the news data before and after the spread of the epidemic, it is possible to see how the direction of crisis management is being structured. In particular, by utilizing big data analysis of international news data, discourses around the world can be analyzed more deeply. This study collected and analyzed 58,061 international news items related to mask-wearing from 1 January 2019 to 31 December 2020. The collected dataset was compared before and after the World Health Organization’s pandemic declaration by applying structural topic model analysis. The results revealed that prior to the declaration, issues related to the COVID-19 outbreak were emphasized, but afterward, issues related to movement restrictions, quarantine management, and local economic impacts emerged. View Full-Text
Keywords: structural topic model; International newspaper; quarantine; mask-wearing; COVID-19 structural topic model; International newspaper; quarantine; mask-wearing; COVID-19
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MDPI and ACS Style

Lee, K.R.; Kim, B.; Nan, D.; Kim, J.H. Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data. Int. J. Environ. Res. Public Health 2021, 18, 6432. https://doi.org/10.3390/ijerph18126432

AMA Style

Lee KR, Kim B, Nan D, Kim JH. Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data. International Journal of Environmental Research and Public Health. 2021; 18(12):6432. https://doi.org/10.3390/ijerph18126432

Chicago/Turabian Style

Lee, Kyeo R., Byungjun Kim, Dongyan Nan, and Jang H. Kim 2021. "Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data" International Journal of Environmental Research and Public Health 18, no. 12: 6432. https://doi.org/10.3390/ijerph18126432

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