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The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study
Evidence-based intervention and policy strategies to address the recent surge of race-motivated hate crimes and other forms of racism against Asian Americans are essential; however, such efforts have been impeded by a lack of empirical knowledge, e.g., about racism, specifically aimed at the Asian A...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8997488/ https://www.ncbi.nlm.nih.gov/pubmed/35409440 http://dx.doi.org/10.3390/ijerph19073757 |
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author | Cao, Jiepin Lee, Chiyoung Sun, Wenyang De Gagne, Jennie C. |
author_facet | Cao, Jiepin Lee, Chiyoung Sun, Wenyang De Gagne, Jennie C. |
author_sort | Cao, Jiepin |
collection | PubMed |
description | Evidence-based intervention and policy strategies to address the recent surge of race-motivated hate crimes and other forms of racism against Asian Americans are essential; however, such efforts have been impeded by a lack of empirical knowledge, e.g., about racism, specifically aimed at the Asian American population. Our qualitative descriptive study sought to fill this gap by using a data-mining approach to examine the contents of tweets having the hashtag #StopAsianHate. We collected tweets during a two-week time frame starting on 20 May 2021, when President Joe Biden signed the COVID-19 Hate Crimes Act. Screening of the 31,665 tweets collected revealed that a total of 904 tweets were eligible for thematic analysis. Our analysis revealed five themes: “Asian hate is not new”, “Address the harm of racism”, “Get involved in #StopAsianHate”, “Appreciate the Asian American and Pacific Islander (AAPI) community’s culture, history, and contributions” and “Increase the visibility of the AAPI community.” Lessons learned from our findings can serve as a foundation for evidence-based strategies to address racism against Asian Americans both locally and globally. |
format | Online Article Text |
id | pubmed-8997488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89974882022-04-12 The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study Cao, Jiepin Lee, Chiyoung Sun, Wenyang De Gagne, Jennie C. Int J Environ Res Public Health Article Evidence-based intervention and policy strategies to address the recent surge of race-motivated hate crimes and other forms of racism against Asian Americans are essential; however, such efforts have been impeded by a lack of empirical knowledge, e.g., about racism, specifically aimed at the Asian American population. Our qualitative descriptive study sought to fill this gap by using a data-mining approach to examine the contents of tweets having the hashtag #StopAsianHate. We collected tweets during a two-week time frame starting on 20 May 2021, when President Joe Biden signed the COVID-19 Hate Crimes Act. Screening of the 31,665 tweets collected revealed that a total of 904 tweets were eligible for thematic analysis. Our analysis revealed five themes: “Asian hate is not new”, “Address the harm of racism”, “Get involved in #StopAsianHate”, “Appreciate the Asian American and Pacific Islander (AAPI) community’s culture, history, and contributions” and “Increase the visibility of the AAPI community.” Lessons learned from our findings can serve as a foundation for evidence-based strategies to address racism against Asian Americans both locally and globally. MDPI 2022-03-22 /pmc/articles/PMC8997488/ /pubmed/35409440 http://dx.doi.org/10.3390/ijerph19073757 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cao, Jiepin Lee, Chiyoung Sun, Wenyang De Gagne, Jennie C. The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title | The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title_full | The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title_fullStr | The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title_full_unstemmed | The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title_short | The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study |
title_sort | #stopasianhate movement on twitter: a qualitative descriptive study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8997488/ https://www.ncbi.nlm.nih.gov/pubmed/35409440 http://dx.doi.org/10.3390/ijerph19073757 |
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