JMIR Publications

ABSTRACT

Background:

Anti-Asian hate crimes escalated during the COVID-19 pandemic; however, limited research has explored the association between social media sentiment and hate crimes toward Asian communities.

Objective:

To investigate the relationship between Twitter sentiment data and the occurrence of anti-Asian hate crimes in New York City from 2019 to 2022, a period encompassing both pre-and-during-COVID conditions.

Methods:

We utilized a hate crime dataset from the New York City Police Department and measured sentiment toward Asians using the rates of negative and positive sentiment expressed in tweets at the monthly level (N = 48). We used negative binomial models to explore the associations between sentiment levels and hate crimes.

Results:

One percentage point increase in the proportion of tweets referencing Asians that were negative was associated with a 24% increase (IRR: 1.24; 95% CI: 1.07, 1.44) in the number of anti-Asian hate crimes in the same month. The significant association was slightly attenuated after adjusting for unemployment and COVID-19 emergence (i.e., after March 2020). The proportion of tweets referencing Asians were positive was associated with a 12% decrease (IRR: 0.88; 95% CI: 0.79, 0.97) in expected anti-Asian hate crimes in the same month but the relationship was no longer significant after adjusting for unemployment rate and the emergence of COVID-19.

Conclusions:

A higher negative sentiment level was associated with more hate crimes specifically targeting the Asian community in the same month. The findings highlight the importance of monitoring public sentiment to predict and potentially mitigate hate crimes against Asians.