A hate crime, according to the FBI, is “a traditional offense like murder, arson, or vandalism with an added element of bias” (https://www.fbi.gov/investigate/civil-rights/hate-crimes).
Let’s focus first on the idea of bias. It’s exceedingly clear that COVID-19 has illuminated bias and prejudice via the entrenchment of structural and institutional inequities. Rooting the discussion of bias in the treatment of the AAPI community requires a close look at former President Trump’s abysmal handling of the pandemic in its early days and the racial/ethnic tensions incited by Trump and his administration.
In late June at a rally in Phoenix, Trump referred to COVID as “kung flu,” prompting outrage from the public and from Asian American groups. Vitriolic rhetoric on Twitter further contributed to anti-Asian sentiment and undoubtedly contributed to the spread of racist hashtags like “#chinesevirus” and “#kungflu.” A research article in the Journal of Medical Internet Research attempted to quantify racially charged epithets in the Twittersphere, finding that “A total of 16,535 “Chinese virus” or “China virus” tweets were identified in the preperiod, and 177,327 tweets were identified in the postperiod, illustrating a nearly ten-fold increase at the national level” (https://www.jmir.org/2020/5/e19301/).
The figure below, created by Foothill Scientia using the R programming language, depicts the 5 states with the greatest percentage increase in “‘Chinese Virus’ tweets” comparing the time-period of 3/9-3/15 to 3/19-3/25.
As shown in the figure, Idaho had the highest percent increase of 1457%, although the prevalence of racist tweets increased in all 50 states.
The video below from TODAY takes a narrative approach to understanding hate crimes against the AAPI community and also discusses the Stop AAPI Hate reporting system.
This is the first segment of Foothill Scientia’s data journalism project, AAPI Convergence. Stay tuned for our upcoming articles and data-driven insights.