RT Article
T1 Questing for Justice on Twitter: topic Modeling of #StopAsianHate Discourses in the Wake of Atlanta Shooting
JF Crime & delinquency
VO 69
IS 13/14
SP 2874
OP 2900
A1 Lee, Claire Seungeun
A2 Jang, Ahnlee
LA English
YR 2023
UL https://krimdok.uni-tuebingen.de/Record/1869155696
AB On March 16, 2021, a shooting in Atlanta killed eight people, six were women of Asian descent. This creates a new atmosphere online and offline to discuss hate crimes, racism, and violence against Asian Americans in the United States. The current research utilizes structural topic modeling and text mining to explore how the 2021 Atlanta shooting ignited debates and public discourse on the #StopAsianHate-related conversations on Twitter. The study analyzes the first 7?days of the shooting to explore the temporal patterns and emergent topics of Twitter discourses. Findings show that salient topics and temporal patterns differ from day to day, but topics such as ?stand with AAPI community? and ?stop racism? are prevalent throughout the 7-day period. This study discusses social media?s role in shaping and reporting public discourses, that is, how digital justice is exercised, and offers social and policy implications. There can be implications for social media?s role in shaping and reporting public discourses on social phenomena with digital justice.
K1 #StopAsianHate
K1 Twitter
K1 anti-Asian hate crime and violence
K1 social media activism
K1 topic modeling
DO 10.1177/00111287211057855