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Information networks for COVID-19 according to race/ethnicity
This study highlights information networks for COVID-19 according to race/ethnicity by employing social network analysis for Twitter. First, this study finds that racial/ethnic groups are differently dependent on racial/ethnic key players. Whites and Asians show the highest number of racial/ethnic k...
Autor principal: | |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034768/ https://www.ncbi.nlm.nih.gov/pubmed/37124836 http://dx.doi.org/10.1007/s10799-022-00360-0 |
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author | Yum, Seungil |
author_facet | Yum, Seungil |
author_sort | Yum, Seungil |
collection | PubMed |
description | This study highlights information networks for COVID-19 according to race/ethnicity by employing social network analysis for Twitter. First, this study finds that racial/ethnic groups are differently dependent on racial/ethnic key players. Whites and Asians show the highest number of racial/ethnic key players, Hispanics have a racial/ethnic key player, and blacks have no racial/ethnic key player in the top 20. Second, racial/ethnic groups show different characteristics of information resources for COVID-19. Whites have the highest key player group in news media, politicians, and researchers, and blacks show the highest key player group in news media. Asians demonstrate the highest key player group in news media, and Hispanics exhibit institutes as the highest key player group. Lastly, there are some differences in group communications across the race/ethnicity. Whites and blacks show open communication systems, whereas Asians and Hispanics reveal closed communication systems. Therefore, governments should understand the characteristics of communications for COVID-19 according to the race/ethnicity. |
format | Online Article Text |
id | pubmed-9034768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-90347682022-04-25 Information networks for COVID-19 according to race/ethnicity Yum, Seungil Inf Technol Manag Article This study highlights information networks for COVID-19 according to race/ethnicity by employing social network analysis for Twitter. First, this study finds that racial/ethnic groups are differently dependent on racial/ethnic key players. Whites and Asians show the highest number of racial/ethnic key players, Hispanics have a racial/ethnic key player, and blacks have no racial/ethnic key player in the top 20. Second, racial/ethnic groups show different characteristics of information resources for COVID-19. Whites have the highest key player group in news media, politicians, and researchers, and blacks show the highest key player group in news media. Asians demonstrate the highest key player group in news media, and Hispanics exhibit institutes as the highest key player group. Lastly, there are some differences in group communications across the race/ethnicity. Whites and blacks show open communication systems, whereas Asians and Hispanics reveal closed communication systems. Therefore, governments should understand the characteristics of communications for COVID-19 according to the race/ethnicity. Springer US 2022-04-23 2023 /pmc/articles/PMC9034768/ /pubmed/37124836 http://dx.doi.org/10.1007/s10799-022-00360-0 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Yum, Seungil Information networks for COVID-19 according to race/ethnicity |
title | Information networks for COVID-19 according to race/ethnicity |
title_full | Information networks for COVID-19 according to race/ethnicity |
title_fullStr | Information networks for COVID-19 according to race/ethnicity |
title_full_unstemmed | Information networks for COVID-19 according to race/ethnicity |
title_short | Information networks for COVID-19 according to race/ethnicity |
title_sort | information networks for covid-19 according to race/ethnicity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034768/ https://www.ncbi.nlm.nih.gov/pubmed/37124836 http://dx.doi.org/10.1007/s10799-022-00360-0 |
work_keys_str_mv | AT yumseungil informationnetworksforcovid19accordingtoraceethnicity |