Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach [article]

Lei Gao, Alexis Kuppersmith, Ruihong Huang
2018 arXiv   pre-print
In the wake of a polarizing election, social media is laden with hateful content. To address various limitations of supervised hate speech classification methods including corpus bias and huge cost of annotation, we propose a weakly supervised two-path bootstrapping approach for an online hate speech detection model leveraging large-scale unlabeled data. This system significantly outperforms hate speech detection systems that are trained in a supervised manner using manually annotated data.
more » ... ying this model on a large quantity of tweets collected before, after, and on election day reveals motivations and patterns of inflammatory language.
arXiv:1710.07394v2 fatcat:te3sqzclpbbqpo67mmq4w247ni