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The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms
BACKGROUND: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people. OBJECTIVE: This study examines public engagement in crisis communication...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674145/ https://www.ncbi.nlm.nih.gov/pubmed/33156807 http://dx.doi.org/10.2196/22639 |
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author | Hu, Zhiwen Yang, Zhongliang Li, Qi Zhang, An |
author_facet | Hu, Zhiwen Yang, Zhongliang Li, Qi Zhang, An |
author_sort | Hu, Zhiwen |
collection | PubMed |
description | BACKGROUND: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people. OBJECTIVE: This study examines public engagement in crisis communication about COVID-19 during the early epidemic stage and the practical strategy of social mobilization to mitigate the infodemic. METHODS: We retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020, which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior. RESULTS: People around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the official names. Many stigmatized monikers against China (eg, “Wuhan pneumonia,” G=0.73; “Wuhan coronavirus,” G=0.60; “China pneumonia,” G=0.59; “China coronavirus,” G=0.52; “Chinese coronavirus,” G=0.50) had high collective heterogeneity of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms “COVID-19” (G=0.44) and “SARS-CoV-2” (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same mission but in diverse voices. CONCLUSIONS: Infodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors, which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic. |
format | Online Article Text |
id | pubmed-7674145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-76741452020-11-20 The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms Hu, Zhiwen Yang, Zhongliang Li, Qi Zhang, An J Med Internet Res Original Paper BACKGROUND: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people. OBJECTIVE: This study examines public engagement in crisis communication about COVID-19 during the early epidemic stage and the practical strategy of social mobilization to mitigate the infodemic. METHODS: We retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020, which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior. RESULTS: People around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the official names. Many stigmatized monikers against China (eg, “Wuhan pneumonia,” G=0.73; “Wuhan coronavirus,” G=0.60; “China pneumonia,” G=0.59; “China coronavirus,” G=0.52; “Chinese coronavirus,” G=0.50) had high collective heterogeneity of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms “COVID-19” (G=0.44) and “SARS-CoV-2” (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same mission but in diverse voices. CONCLUSIONS: Infodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors, which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic. JMIR Publications 2020-11-16 /pmc/articles/PMC7674145/ /pubmed/33156807 http://dx.doi.org/10.2196/22639 Text en ©Zhiwen Hu, Zhongliang Yang, Qi Li, An Zhang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.11.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Hu, Zhiwen Yang, Zhongliang Li, Qi Zhang, An The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title | The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title_full | The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title_fullStr | The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title_full_unstemmed | The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title_short | The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms |
title_sort | covid-19 infodemic: infodemiology study analyzing stigmatizing search terms |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674145/ https://www.ncbi.nlm.nih.gov/pubmed/33156807 http://dx.doi.org/10.2196/22639 |
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