Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective
Objective: This pilot study aimed to examine the content of Japanese newspaper editorials concerning the coronavirus disease 2019 (COVID-19) pandemic and its change over time using text mining analysis. Materials and Methods: The authors analyzed qualitative data from the editorials of five national...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Japanese Association of Rural Medicine
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613367/ https://www.ncbi.nlm.nih.gov/pubmed/36397798 http://dx.doi.org/10.2185/jrm.2021-063 |
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author | Maeda, Wakae Hirakawa, Yoshihisa Muraya, Tsukasa Miura, Hisayuki |
author_facet | Maeda, Wakae Hirakawa, Yoshihisa Muraya, Tsukasa Miura, Hisayuki |
author_sort | Maeda, Wakae |
collection | PubMed |
description | Objective: This pilot study aimed to examine the content of Japanese newspaper editorials concerning the coronavirus disease 2019 (COVID-19) pandemic and its change over time using text mining analysis. Materials and Methods: The authors analyzed qualitative data from the editorials of five national and 12 regional newspapers on April 7 and 8, 2020 (first state of emergency) and January 8, 2021 (second state of emergency). All analyses were conducted using KH Coder version 3. Results: The co-occurrence network showed a low level of content diversity and a high degree of politicization in the COVID-19 news coverage. The top five high frequency words from the newspapers were “infection”, “declaration”, “healthcare”, “government”, and “emergency” at the first state of emergency, and were “declaration”, “measures”, “government”, and “restaurant” at the second one. Conclusion: The results suggest a lack of detailed information and recommendations concerning the public health challenges of the COVID-19 pandemic in Japanese newspaper editorials, even one year after the first wave of the pandemic. This study provides a data-driven foundation for the effectiveness of newspapers in COVID-19 public health communications. The extent to which the quantity and quality of information from newly emerging communication channels, such as social media, influences public understanding of public health measures remains to be established. |
format | Online Article Text |
id | pubmed-9613367 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Japanese Association of Rural Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-96133672022-11-16 Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective Maeda, Wakae Hirakawa, Yoshihisa Muraya, Tsukasa Miura, Hisayuki J Rural Med Letters to the Editor Objective: This pilot study aimed to examine the content of Japanese newspaper editorials concerning the coronavirus disease 2019 (COVID-19) pandemic and its change over time using text mining analysis. Materials and Methods: The authors analyzed qualitative data from the editorials of five national and 12 regional newspapers on April 7 and 8, 2020 (first state of emergency) and January 8, 2021 (second state of emergency). All analyses were conducted using KH Coder version 3. Results: The co-occurrence network showed a low level of content diversity and a high degree of politicization in the COVID-19 news coverage. The top five high frequency words from the newspapers were “infection”, “declaration”, “healthcare”, “government”, and “emergency” at the first state of emergency, and were “declaration”, “measures”, “government”, and “restaurant” at the second one. Conclusion: The results suggest a lack of detailed information and recommendations concerning the public health challenges of the COVID-19 pandemic in Japanese newspaper editorials, even one year after the first wave of the pandemic. This study provides a data-driven foundation for the effectiveness of newspapers in COVID-19 public health communications. The extent to which the quantity and quality of information from newly emerging communication channels, such as social media, influences public understanding of public health measures remains to be established. The Japanese Association of Rural Medicine 2022-10-22 2022-10 /pmc/articles/PMC9613367/ /pubmed/36397798 http://dx.doi.org/10.2185/jrm.2021-063 Text en ©2022 The Japanese Association of Rural Medicine https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ). |
spellingShingle | Letters to the Editor Maeda, Wakae Hirakawa, Yoshihisa Muraya, Tsukasa Miura, Hisayuki Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title | Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title_full | Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title_fullStr | Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title_full_unstemmed | Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title_short | Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective |
title_sort | text mining analysis of newspaper editorials concerning the covid-19 pandemic from a healthcare perspective |
topic | Letters to the Editor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613367/ https://www.ncbi.nlm.nih.gov/pubmed/36397798 http://dx.doi.org/10.2185/jrm.2021-063 |
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