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Investigating COVID-19 News before and after the Soft Lockdown: An Example from Taiwan

Hsin-Yu Kuo (), Su-Yen Chen () and Yu-Ting Lai ()
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Hsin-Yu Kuo: Department of Educational Psychology and Counseling, National Tsing Hua University, Hsinchu 30013, Taiwan
Su-Yen Chen: Institute of Learning Sciences and Technologies, National Tsing Hua University, Hsinchu 30013, Taiwan
Yu-Ting Lai: International Intercollegiate Ph.D. Program (IPHD), National Tsing Hua University, Hsinchu 30013, Taiwan

Sustainability, 2021, vol. 13, issue 20, 1-23

Abstract: COVID-19 caused an unprecedented public health crisis and was declared a global pandemic on 11 March 2020, by the World Health Organization. The Taiwanese government’s early deployment mitigated the effect of the pandemic, yet the breakout in May 2021 brought a new challenge. This study focuses on examining Taiwanese newspaper articles regarding the government response before and after the soft lockdown, collecting 125,570 articles reported by three major news channels from 31 December 2019, to 30 June 2021, and splitting them into four stages. Latent Dirichlet Allocation topic modeling and sentiment analysis were used to depict the overall picture of Taiwan’s pandemic. While the news media focused on the impact and shock of the pandemic in the initial stage, prevention measures were more present in the last stage. Then, to focus on the government response indicators, we retrieved 31,089 related news from 125,570 news articles and categorized them into ten indicators, finding the news centered on the fundamental measures that were taken early and that were transformed into advanced measures in the latest and hardest period of the pandemic. Furthermore, this paper examines the temporal distribution of the news related to each indicator with the support of a sentiment analysis of the news’ titles and content, indicating the preparation of Taiwanese society to confront the pandemic.

Keywords: COVID-19 pandemic; newspaper; government response; text mining; LDA; sentiment analysis; Taiwan (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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