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Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter

OBJECTIVES: This study analyzed the perceptions and emotions of Korean and Japanese citizens regarding coronavirus disease 2019 (COVID-19). It examined the frequency of words used in Korean and Japanese tweets regarding COVID-19 and the corresponding changes in their interests. METHODS: This cross-s...

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Autores principales: Lee, Hocheol, Noh, Eun Bi, Choi, Sea Hwan, Zhao, Bo, Nam, Eun Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674818/
https://www.ncbi.nlm.nih.gov/pubmed/33190468
http://dx.doi.org/10.4258/hir.2020.26.4.335
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author Lee, Hocheol
Noh, Eun Bi
Choi, Sea Hwan
Zhao, Bo
Nam, Eun Woo
author_facet Lee, Hocheol
Noh, Eun Bi
Choi, Sea Hwan
Zhao, Bo
Nam, Eun Woo
author_sort Lee, Hocheol
collection PubMed
description OBJECTIVES: This study analyzed the perceptions and emotions of Korean and Japanese citizens regarding coronavirus disease 2019 (COVID-19). It examined the frequency of words used in Korean and Japanese tweets regarding COVID-19 and the corresponding changes in their interests. METHODS: This cross-sectional study analyzed Twitter posts (Tweets) from February 1, 2020 to April 30, 2020 to determine public opinion of the COVID-19 pandemic in Korea and Japan. We collected data from Twitter (https://twitter.com/), a major social media platform in Korea and Japan. Python 3.7 Library was used for data collection. Data analysis included KR-WordRank and frequency analyses in Korea and Japan, respectively. Heat diagrams, word clouds, and rank flowcharts were also used. RESULTS: Overall, 1,470,673 and 4,195,457 tweets were collected from Korea and Japan, respectively. The word trend in Korea and Japan was analyzed every 5 days. The word cloud analysis revealed “COVID-19”, “Shinchonji”, “Mask”, “Daegu”, and “Travel” as frequently used words in Korea. While in Japan, “COVID-19”, “Mask”, “Test”, “Impact”, and “China” were identified as high-frequency words. They were divided into four categories: social distancing, prevention, issue, and emotion for the rank flowcharts. Concerning emotion, “Overcome” and “Support” increased from February in Korea, while “Worry” and “Anxiety” decreased in Japan from April 1. CONCLUSIONS: As a result of the trend, people’s interests in the economy were high in both countries, indicating their reservations on the economic down-turn. Therefore, focusing policies toward economic stability is essential. Although the interest in prevention increased since April in both countries, the general public’s relaxation regarding COVID-19 was also observed.
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spelling pubmed-76748182020-11-19 Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter Lee, Hocheol Noh, Eun Bi Choi, Sea Hwan Zhao, Bo Nam, Eun Woo Healthc Inform Res Original Article OBJECTIVES: This study analyzed the perceptions and emotions of Korean and Japanese citizens regarding coronavirus disease 2019 (COVID-19). It examined the frequency of words used in Korean and Japanese tweets regarding COVID-19 and the corresponding changes in their interests. METHODS: This cross-sectional study analyzed Twitter posts (Tweets) from February 1, 2020 to April 30, 2020 to determine public opinion of the COVID-19 pandemic in Korea and Japan. We collected data from Twitter (https://twitter.com/), a major social media platform in Korea and Japan. Python 3.7 Library was used for data collection. Data analysis included KR-WordRank and frequency analyses in Korea and Japan, respectively. Heat diagrams, word clouds, and rank flowcharts were also used. RESULTS: Overall, 1,470,673 and 4,195,457 tweets were collected from Korea and Japan, respectively. The word trend in Korea and Japan was analyzed every 5 days. The word cloud analysis revealed “COVID-19”, “Shinchonji”, “Mask”, “Daegu”, and “Travel” as frequently used words in Korea. While in Japan, “COVID-19”, “Mask”, “Test”, “Impact”, and “China” were identified as high-frequency words. They were divided into four categories: social distancing, prevention, issue, and emotion for the rank flowcharts. Concerning emotion, “Overcome” and “Support” increased from February in Korea, while “Worry” and “Anxiety” decreased in Japan from April 1. CONCLUSIONS: As a result of the trend, people’s interests in the economy were high in both countries, indicating their reservations on the economic down-turn. Therefore, focusing policies toward economic stability is essential. Although the interest in prevention increased since April in both countries, the general public’s relaxation regarding COVID-19 was also observed. Korean Society of Medical Informatics 2020-10 2020-10-31 /pmc/articles/PMC7674818/ /pubmed/33190468 http://dx.doi.org/10.4258/hir.2020.26.4.335 Text en © 2020 The Korean Society of Medical Informatics This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Lee, Hocheol
Noh, Eun Bi
Choi, Sea Hwan
Zhao, Bo
Nam, Eun Woo
Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title_full Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title_fullStr Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title_full_unstemmed Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title_short Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter
title_sort determining public opinion of the covid-19 pandemic in south korea and japan: social network mining on twitter
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674818/
https://www.ncbi.nlm.nih.gov/pubmed/33190468
http://dx.doi.org/10.4258/hir.2020.26.4.335
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