Detecting East Asian Prejudice on Social Media
This addresses the spread of hateful language online, specifically targeting East Asian prejudice, with potential applications in content moderation and research, though it is incremental as it applies existing methods to a new dataset.
The paper tackles the problem of detecting and categorizing East Asian prejudice on social media during COVID-19 by creating a classifier for Twitter posts, achieving an F1 score of 0.83 across four classes.
The outbreak of COVID-19 has transformed societies across the world as governments tackle the health, economic and social costs of the pandemic. It has also raised concerns about the spread of hateful language and prejudice online, especially hostility directed against East Asia. In this paper we report on the creation of a classifier that detects and categorizes social media posts from Twitter into four classes: Hostility against East Asia, Criticism of East Asia, Meta-discussions of East Asian prejudice and a neutral class. The classifier achieves an F1 score of 0.83 across all four classes. We provide our final model (coded in Python), as well as a new 20,000 tweet training dataset used to make the classifier, two analyses of hashtags associated with East Asian prejudice and the annotation codebook. The classifier can be implemented by other researchers, assisting with both online content moderation processes and further research into the dynamics, prevalence and impact of East Asian prejudice online during this global pandemic.