@article{ref1,
title="The #StopAsianHate movement on Twitter: a qualitative descriptive study",
journal="International journal of environmental research and public health",
year="2022",
author="Cao, Jiepin and Lee, Chiyoung and Sun, Wenyang and De Gagne, Jennie C.",
volume="19",
number="7",
pages="e3757-e3757",
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: &quot;Asian hate is not new&quot;, &quot;Address the harm of racism&quot;, &quot;Get involved in #StopAsianHate&quot;, &quot;Appreciate the Asian American and Pacific Islander (AAPI) community's culture, history, and contributions&quot; and &quot;Increase the visibility of the AAPI community.&quot; Lessons learned from our findings can serve as a foundation for evidence-based strategies to address racism against Asian Americans both locally and globally.<p /> <p>Language: en</p>",
language="en",
issn="1661-7827",
doi="10.3390/ijerph19073757",
url="http://dx.doi.org/10.3390/ijerph19073757"
}