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.
| Original language | English (US) |
|---|---|
| Article number | 3757 |
| Journal | International journal of environmental research and public health |
| Volume | 19 |
| Issue number | 7 |
| DOIs | |
| State | Published - Apr 1 2022 |
| Externally published | Yes |
Keywords
- Asian Americans
- Data mining
- Qualitative research
- Social media
ASJC Scopus subject areas
- Pollution
- Public Health, Environmental and Occupational Health
- Health, Toxicology and Mutagenesis
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