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Big Data Analysis of Media Reports Related to COVID-19

COVID-19 is lasting longer than expected, which has a huge impact on the economy and on personal life. Each country has a different response method, and the damage scale is also distinct. This study aims to find out how COVID-19-related news was handled in the domestic media to seek ways to minimize...

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Detalles Bibliográficos
Autores principales: Jung, Ji-Hee, Shin, Jae-Ik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459752/
https://www.ncbi.nlm.nih.gov/pubmed/32781727
http://dx.doi.org/10.3390/ijerph17165688
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author Jung, Ji-Hee
Shin, Jae-Ik
author_facet Jung, Ji-Hee
Shin, Jae-Ik
author_sort Jung, Ji-Hee
collection PubMed
description COVID-19 is lasting longer than expected, which has a huge impact on the economy and on personal life. Each country has a different response method, and the damage scale is also distinct. This study aims to find out how COVID-19-related news was handled in the domestic media to seek ways to minimize the pandemic. The paper focuses on the number of news features by period and by disaster and analyzes related words based on big data. The results of the analysis are as follows. First, in the initial response phase, keywords to identify accurate sources of actual broadcast contents, fake news, social networking service (SNS), etc. were also ranked in the top 20. Second, in the active response phase, when the number of confirmed persons and the government’s countermeasures were announced, more than 100 COVID-19-related articles were issued, and the related words increased rapidly from the initial response stage. Therefore, the fact that COVID-19 has been expressed as a keyword indicates that our society is watching with great interest in the government’s response to the disease.
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spelling pubmed-74597522020-09-02 Big Data Analysis of Media Reports Related to COVID-19 Jung, Ji-Hee Shin, Jae-Ik Int J Environ Res Public Health Article COVID-19 is lasting longer than expected, which has a huge impact on the economy and on personal life. Each country has a different response method, and the damage scale is also distinct. This study aims to find out how COVID-19-related news was handled in the domestic media to seek ways to minimize the pandemic. The paper focuses on the number of news features by period and by disaster and analyzes related words based on big data. The results of the analysis are as follows. First, in the initial response phase, keywords to identify accurate sources of actual broadcast contents, fake news, social networking service (SNS), etc. were also ranked in the top 20. Second, in the active response phase, when the number of confirmed persons and the government’s countermeasures were announced, more than 100 COVID-19-related articles were issued, and the related words increased rapidly from the initial response stage. Therefore, the fact that COVID-19 has been expressed as a keyword indicates that our society is watching with great interest in the government’s response to the disease. MDPI 2020-08-06 2020-08 /pmc/articles/PMC7459752/ /pubmed/32781727 http://dx.doi.org/10.3390/ijerph17165688 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jung, Ji-Hee
Shin, Jae-Ik
Big Data Analysis of Media Reports Related to COVID-19
title Big Data Analysis of Media Reports Related to COVID-19
title_full Big Data Analysis of Media Reports Related to COVID-19
title_fullStr Big Data Analysis of Media Reports Related to COVID-19
title_full_unstemmed Big Data Analysis of Media Reports Related to COVID-19
title_short Big Data Analysis of Media Reports Related to COVID-19
title_sort big data analysis of media reports related to covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459752/
https://www.ncbi.nlm.nih.gov/pubmed/32781727
http://dx.doi.org/10.3390/ijerph17165688
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