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Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data
Kyeo Re Lee1, Byungjun Kim2, Dongyan Nan1,2
1Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul 03063, Korea.
Summary
Media coverage of mask-wearing evolved during the COVID-19 pandemic. Analysis of news data shows a shift from outbreak focus to public health measures like movement restrictions and economic impacts.
Area of Science:
- Public Health
- Media Studies
- Epidemiology
Background:
- Media is a key source of health information globally, especially during pandemics like COVID-19.
- Mask-wearing is a public health measure influenced by cultural perceptions and mandates.
- Analyzing media discourse provides insights into crisis management strategies.
Purpose of the Study:
- To analyze international news discourse on mask-wearing before and after the COVID-19 pandemic declaration.
- To understand shifts in public health communication and crisis management strategies.
Main Methods:
- Big data analysis of 58,061 international news items from January 2019 to December 2020.
- Structural topic modeling to compare news content before and after the World Health Organization's pandemic declaration.
Main Results:
- Pre-declaration news emphasized COVID-19 outbreak issues.
- Post-declaration news highlighted movement restrictions, quarantine management, and local economic impacts.
- Discourse analysis revealed evolving public health priorities and concerns.
Conclusions:
- Media discourse significantly shifted in response to the COVID-19 pandemic declaration.
- The analysis demonstrates the role of media in reflecting and shaping public understanding of health crises and interventions.
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