Factoring Hate Speech: A New Annotation Framework to Study Hate Speech in Social Media
This work addresses the challenge of systematically studying hate speech for researchers and policymakers, though it is incremental as it builds on existing annotation methods.
The authors tackled the problem of analyzing hate speech on social media by proposing a new annotation framework that categorizes hate speech into five discursive categories, and they applied it to a corpus of 2.9M tweets targeting Jews, annotating a sample of 1,050 tweets to provide statistical insights.
In this work we propose a novel annotation scheme which factors hate speech into five separate discursive categories. To evaluate our scheme, we construct a corpus of over 2.9M Twitter posts containing hateful expressions directed at Jews, and annotate a sample dataset of 1,050 tweets. We present a statistical analysis of the annotated dataset as well as discuss annotation examples, and conclude by discussing promising directions for future work.