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Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis

BACKGROUND: When the first COVID-19 cases were noticed in China, many racist comments against Chinese individuals spread. As there is a huge need to better comprehend why all of these targeted comments and opinions developed specifically at the start of the outbreak, we sought to carefully examine r...

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Autores principales: Lloret-Pineda, Amanda, He, Yuelu, Haro, Josep Maria, Cristóbal-Narváez, Paula
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122024/
https://www.ncbi.nlm.nih.gov/pubmed/35446780
http://dx.doi.org/10.2196/29183
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author Lloret-Pineda, Amanda
He, Yuelu
Haro, Josep Maria
Cristóbal-Narváez, Paula
author_facet Lloret-Pineda, Amanda
He, Yuelu
Haro, Josep Maria
Cristóbal-Narváez, Paula
author_sort Lloret-Pineda, Amanda
collection PubMed
description BACKGROUND: When the first COVID-19 cases were noticed in China, many racist comments against Chinese individuals spread. As there is a huge need to better comprehend why all of these targeted comments and opinions developed specifically at the start of the outbreak, we sought to carefully examine racism and advocacy efforts on Twitter in the first quarter of 2020 (January 15 to March 3, 2020). OBJECTIVE: The first research question aimed to understand the main type of racism displayed on Twitter during the first quarter of 2020. The second research question focused on evaluating Twitter users’ positive and negative responses regarding racism toward Chinese individuals. METHODS: Content analysis of tweets was utilized to address the two research questions. Using the NCapture browser link and NVivo software, tweets in English and Spanish were pulled from the Twitter data stream from January 15 to March 3, 2020. A total of 19,150 tweets were captured using the advanced Twitter search engine with the keywords and hashtags #nosoyunvirus, #imNotAVirus, #ChineseDon’tComeToJapan, #racism, “No soy un virus,” and “Racismo Coronavirus.” After cleaning the data, a total of 402 tweets were codified and analyzed. RESULTS: The data confirmed clear sentiments of racism against Chinese individuals during the first quarter of 2020. The tweets displayed individual, cultural, and institutional racism. Individual racism was the most commonly reported form of racism, specifically displaying physical and verbal aggression. As a form of resistance, Twitter users created spaces for advocacy and activism. The hashtag “I am not a virus” helped to break stereotypes, prejudice, and discrimination on Twitter. CONCLUSIONS: Advocacy efforts were enormous both inside and outside the Chinese community; an allyship sentiment was fostered by some white users, and an identification with the oppression experienced by the Chinese population was expressed in the Black and Muslim worldwide communities. Activism through social media manifested through art, food sharing, and community support.
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spelling pubmed-91220242022-05-21 Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis Lloret-Pineda, Amanda He, Yuelu Haro, Josep Maria Cristóbal-Narváez, Paula JMIR Form Res Original Paper BACKGROUND: When the first COVID-19 cases were noticed in China, many racist comments against Chinese individuals spread. As there is a huge need to better comprehend why all of these targeted comments and opinions developed specifically at the start of the outbreak, we sought to carefully examine racism and advocacy efforts on Twitter in the first quarter of 2020 (January 15 to March 3, 2020). OBJECTIVE: The first research question aimed to understand the main type of racism displayed on Twitter during the first quarter of 2020. The second research question focused on evaluating Twitter users’ positive and negative responses regarding racism toward Chinese individuals. METHODS: Content analysis of tweets was utilized to address the two research questions. Using the NCapture browser link and NVivo software, tweets in English and Spanish were pulled from the Twitter data stream from January 15 to March 3, 2020. A total of 19,150 tweets were captured using the advanced Twitter search engine with the keywords and hashtags #nosoyunvirus, #imNotAVirus, #ChineseDon’tComeToJapan, #racism, “No soy un virus,” and “Racismo Coronavirus.” After cleaning the data, a total of 402 tweets were codified and analyzed. RESULTS: The data confirmed clear sentiments of racism against Chinese individuals during the first quarter of 2020. The tweets displayed individual, cultural, and institutional racism. Individual racism was the most commonly reported form of racism, specifically displaying physical and verbal aggression. As a form of resistance, Twitter users created spaces for advocacy and activism. The hashtag “I am not a virus” helped to break stereotypes, prejudice, and discrimination on Twitter. CONCLUSIONS: Advocacy efforts were enormous both inside and outside the Chinese community; an allyship sentiment was fostered by some white users, and an identification with the oppression experienced by the Chinese population was expressed in the Black and Muslim worldwide communities. Activism through social media manifested through art, food sharing, and community support. JMIR Publications 2022-05-19 /pmc/articles/PMC9122024/ /pubmed/35446780 http://dx.doi.org/10.2196/29183 Text en ©Amanda Lloret-Pineda, Yuelu He, Josep Maria Haro, Paula Cristóbal-Narváez. Originally published in JMIR Formative Research (https://formative.jmir.org), 19.05.2022. 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 JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lloret-Pineda, Amanda
He, Yuelu
Haro, Josep Maria
Cristóbal-Narváez, Paula
Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title_full Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title_fullStr Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title_full_unstemmed Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title_short Types of Racism and Twitter Users’ Responses Amid the COVID-19 Outbreak: Content Analysis
title_sort types of racism and twitter users’ responses amid the covid-19 outbreak: content analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122024/
https://www.ncbi.nlm.nih.gov/pubmed/35446780
http://dx.doi.org/10.2196/29183
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