Intersectional Bias in Hate Speech and Abusive Language Datasets

Understand

Algorithms are widely applied to detect hate speech and abusive language in social media.

• We investigated whether the human-annotated data used to train these algorithms are biased.
• We utilized a publicly available annotated Twitter dataset (Founta et al.
• 2018) and classified the racial, gender, and party identification dimensions of 99,996 tweets.