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The #StopAsianHate Movement on Twitter: A Qualitative Descriptive Study.
Cao, Jiepin; Lee, Chiyoung; Sun, Wenyang; De Gagne, Jennie C.
  • Cao J; School of Nursing, Duke University, Durham, NC 27710, USA.
  • Lee C; School of Nursing & Health Studies, University of Washington Bothell, Bothell, WA 98011, USA.
  • Sun W; Department of Education, Culture & Society, The University of Utah, Salt Lake City, UT 84112, USA.
  • De Gagne JC; School of Nursing, Duke University, Durham, NC 27710, USA.
Int J Environ Res Public Health ; 19(7)2022 03 22.
Article in English | MEDLINE | ID: covidwho-1753501
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / Racism / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research / Reviews Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19073757

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / Racism / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research / Reviews Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19073757