Racial bias in hate speech and abusive language detection datasets

A paper on racial bias in hate speech

Technologies for abusive language detection are being developed and applied with little consideration of their potential biases. We examine racial bias in five different sets of Twitter data annotated for hate speech and abusive language.

Tweets written in African-American English are far more likely to be automatically classified as abusive or containing hate speech.