Citation

Cao J, Lee C, Sun W, De Gagne JC. Int. J. Environ. Res. Public Health 2022; 19(7): e3757.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph19073757

PMID

35409440

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.

Language: en

Keywords

data mining; social media; qualitative research; Asian Americans