To drill down on anti-Asian hate crimes, Rochester researchers harness social media

University of Rochester

Rochester researchers use Twitter to gauge public opinion toward #StopAsianHate.

In a new study, University of Rochester researchers refine how information gleaned from Twitter users can be used to document public reaction to attacks on Chinese and other Asians in the US in the wake of COVID-19.

Specifically, they examine public opinion toward #StopAsianHate and #StopAAPIHate, the hashtags and websites that provide information, resources, places to donate, and places to report hate crimes.

In a paper posted at arXiv, an open-access, non-peer-reviewed repository of scientific papers, the researchers find that:

  • The growing political divide in the US extends to this issue, with Biden supporters more likely to support the hashtags, and Trump supporters more likely to be negative.
  • Black and white communities tend to divide over this issue as well, pointing to each other as the ones to be blamed for anti-Asian hate crimes. Black Twitter users, for example, are more likely to discuss their solidarity with the Asian community and tend to retweet messages that criticize white supremacy.
  • The hashtags attract more participation from women and younger adults, and from Asian and Black communities.
  • Women are more likely to state direct support and demand policy changes than men, who tend to discuss the issue in more general ways.
  • The hashtags receive more support in states with higher percentages of Asian populations and a higher incidence of racially motivated hate crimes.

The findings are based on postings by 46,058 Twitter users, across 30 states, between March 18 and April 11 of this year.

“Our interest is to always understand public opinion first, and then maybe discover some insight into how the situation can be improved,” says Jiebo Luo, professor of computer science and the corresponding author. “We hope these findings can help us design better ways of removing tension and misunderstandings between ethnic groups. That’s the high-level objective.”

Luo’s research group has conducted similar studies that mine Twitter to explore public opinion about recent or unfolding events. Last year, the researchers showed how the increased use of terms like “Chinese virus” and “Wuhan virus” on the social media platform correlated strongly with a rise in media reports of attacks on Chinese and other Asians or Asian Americans.

Lead author Bruce Lyu, a PhD student in Luo’s group, says the latest paper is “to the best of our knowledge” the first large-scale social-media based study to examine public opinion about the two Asian anti-hate-crime hashtags. Tweets spiked sharply after the March 16, 2021, shootings in Atlanta, in which six of the eight fatalities involved Asian women.

Other collaborators include Mayya Komisarchik, assistant professor of political science with a focus on race and ethnic politics, and Yangxin Fan and Ziyu Xiong, both master’s students at the Goergen Institute for Data Science.

Komisarchik says academic researchers and pollsters have only recently begun to focus their studies of public opinion among racial and ethnic groups even more narrowly on country of origin.

“Only now are people asking Korean Americans and Chinese Americans and Indonesian Americans what they think about issues-and finding that there are important differences there.”

Komisarchik, who emigrated to the US from Russia, says one focus of her research is immigration “as its own kind of force. Development of political identity is different for those who emigrate here, compared to those who were born here.”

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