This paper is in the following e-collection/theme issue:

Public (e)Health, Digital Epidemiology and Public Health Informatics (871) Infodemiology and Infoveillance (1468) Violence including Domestic Violence/Abuse (135) Systemic Racism and Racial Bias in Health Care and Society (102) Behavioural Surveillance for Public Health (259) Mass Media/Social Media Communication and Campaigns (517) Equity and Digital Divide (286)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53050, first published .
From Tweets to Streets: Observational Study on the Association Between Twitter Sentiment and Anti-Asian Hate Crimes in New York City from 2019 to 2022

From Tweets to Streets: Observational Study on the Association Between Twitter Sentiment and Anti-Asian Hate Crimes in New York City from 2019 to 2022

From Tweets to Streets: Observational Study on the Association Between Twitter Sentiment and Anti-Asian Hate Crimes in New York City from 2019 to 2022

Authors of this article:

Hanxue Wei1 Author Orcid Image ;   Yulin Hswen2 Author Orcid Image ;   Junaid S Merchant3 Author Orcid Image ;   Laura B Drew3 Author Orcid Image ;   Quynh C Nguyen3 Author Orcid Image ;   Xiaohe Yue3 Author Orcid Image ;   Heran Mane3 Author Orcid Image ;   Thu T Nguyen3 Author Orcid Image
Article Authors Cited by (1) Tweetations (1) Metrics

Journals

  1. Nguyen T, Yue X, Mane H, Seelman K, Mullaputi P, Dennard E, Alibilli A, Merchant J, Criss S, Hswen Y, Nguyen Q. Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study. Journal of Medical Internet Research 2025;27:e72822 View