Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19

Pei, Xin; Mehta, Deval

doi:10.1109/bigdata52589.2021.9671945

Cited by 3 publications

(6 citation statements)

References 17 publications

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“…The bill’s passage was a response to a rise in anti-Asian hate crimes during 2020 (Center for the Study of Hate and Extremism 2021) and the fatal shootings in March 2021 of eight women in Atlanta, six of them of Asian origin ( New York Times 2021). These trends coincided with growing online expressions of anti-Asian sentiment (e.g., Pei and Mehta 2020).…”

Section: Introductionmentioning

confidence: 70%

“…Other research on the COVID-19 pandemic has documented a rise in anti-Asian hate incidents (Center for the Study of Hate and Extremism 2021; Jeung et al 2021) and online expressions of anti-Asian sentiment (Lu and Sheng 2022; Nguyen et al 2020; Pei and Mehta 2020; Stechemesser et al 2020; Tahmasbi et al 2021; Zhang et al 2021). Our findings document a more quotidian form of discrimination, resembling the kinds of behaviors that Chinese and Asian Americans are more likely to encounter than physical violence.…”

Section: Discussionmentioning

confidence: 99%

“…Individuals—and perhaps especially those who were attentive to rhetoric from right-wing elites—may have fused anxiety about COVID-19 with prejudice toward people of Asian, and especially Chinese, origin, “a stigmatized group framed as responsible for the disease” (Reny and Barreto 2020: p. 2). Supporting this account, Lu and Sheng (2022) find that each additional tweet related to China and COVID-19 from Donald Trump in one hour predicted a 20% increase in tweets that used a slur for Chinese people in the following four hours (also see Pei and Mehta 2020). In addition, each such tweet from Donald Trump predicted an 8% increase in hate incidents reported to Stop AAPI Hate the following day.…”

Section: Introductionmentioning

confidence: 95%

“…These trends coincided with rising expressions of anti-Asian sentiment online. Multiple studies looking at the first half of 2020 documented increasingly Sinophobic language on English language and U.S. Twitter (Lu and Sheng 2022; Nguyen et al 2020; Pei and Mehta 2020; Stechemesser et al 2020; Tahmasbi et al 2021), Reddit (Zhang et al 2021), and 4chan (Tahmasbi et al 2021). These trends picked up in response to certain news events, including a speech on March 16 2020 in which President Trump first referred to COVID-19 as the “Chinese virus” (Lu and Sheng 2022; Pei and Mehta 2020; also see Rizzuto 2020).…”

Section: Introductionmentioning

confidence: 99%

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Politics, not Vulnerability: Republicans Discriminated against Chinese-born Americans throughout the COVID-19 Pandemic

Abascal

Makovi

Yao

2023

J. Race Ethnicity Politics

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Asian Americans became targets of increasingly hostile behavior during the COVID-19 pandemic. What motivated this? Fears of contagion arising from a behavioral immune system may have motivated hostility toward Asian Americans, especially among those Americans vulnerable to COVID-19. Additionally, stigmatizing rhetoric from right-wing figures may have legitimated anti-Asian behavior among those Americans who held stronger anti-Asian sentiments to begin with or who were more receptive to right-wing rhetoric. We explore these possibilities using a behavioral game with a representative sample of Americans at two points: in May and October 2020. Participants were partnered with a U.S.- or Chinese-born American in a give-or-take dictator game. The average American discriminated against Chinese-born Americans in May but not October 2020, when China was no longer a COVID-19 hotspot. But among Republicans, who may have held stronger anti-Asian sentiments to begin with and who were likely more receptive to right-wing rhetoric, discrimination—that is, differential treatment—was both stronger in May compared to non-Republicans and persisted into October 2020. Notably, Americans who were more vulnerable to COVID-19 were not especially likely to discriminate.

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Section: Introductionmentioning

confidence: 70%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Politics, not Vulnerability: Republicans Discriminated against Chinese-born Americans throughout the COVID-19 Pandemic

Abascal

Makovi

Yao

2023

J. Race Ethnicity Politics

View full text Add to dashboard Cite

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“…Anti-Asian content has strikingly increased on social media since the COVID-19 outbreak. The number of tweets that contain the racist naming of COVID-19 rapidly grew (Chou and Gaysynsky 2021;Pei and Mehta 2020). For example, the number of these tweets increased by a factor of 10 in March 2020 (Budhwani and Sun 2020).…”

Section: Existing Studies On Covid-19-induced Xenophobiamentioning

confidence: 99%

Disease, Scapegoating, and Social Contexts: Examining Social Contexts of the Support for Racist Naming of COVID-19 on Twitter

2023

J Health Soc Behav

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In early 2020, when COVID-19 began to spread in the United States, many Twitter users called it the “Chinese virus,” blaming racial outgroups for the pandemic. I collected tweets containing the “Chinese virus” derivatives posted from March to August 2020 by users within the United States and created a data set with 141,290 tweets published by 50,695 users. I calculated the ratio of users who supported the racist naming of COVID-19 per county and merged Twitter data with the county-level census. Multilevel regression models show that counties with higher COVID-19 mortality or infection rates have more support for the racist naming. Second, the mortality and infection rates effects are stronger in counties with faster minority growth. Moreover, it is mainly in poor counties that minority growth enlarges the effects of infection and mortality rates. These findings relate to the theories on disease-induced xenophobia and the debate between conflict and contact theories.

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Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics

2022

Advances in Data Mining and Database Management

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Racism and physical attacks on Asian communities have spread in the U.S. and around the world. Xenophobia is a virus that may lead to an ongoing social problem in the post-pandemic era. Although existing studies have been done to classify anti-Asian haters, little is known on monitoring, tracking, and characterizing anti-Asian haters on social media platforms. In this chapter, a systematic examination of anti-Asian haters tracking and profiling methods is designed by using big data analytics with deep learning algorithms. Target haters are investigated and tracked by analyzing public opinions towards key topics in 2020, including the U.S. elections, stimulus checks, and economy opening strategies throughout data collection and preprocessing, text classification, sentiment analysis, data visualization, and association rule. Such a comprehensive study provides a variety of research opportunities in dealing with anti-Asian racism and xenophobia in and after the COVID-19 pandemic.

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Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19

Cited by 3 publications

References 17 publications

Politics, not Vulnerability: Republicans Discriminated against Chinese-born Americans throughout the COVID-19 Pandemic

Politics, not Vulnerability: Republicans Discriminated against Chinese-born Americans throughout the COVID-19 Pandemic

Disease, Scapegoating, and Social Contexts: Examining Social Contexts of the Support for Racist Naming of COVID-19 on Twitter

Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics

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