Measuring Hate Speech

Link to publication:

Link to data:

Task description: 10 ordinal labels (sentiment, (dis)respect, insult, humiliation, inferior status, violence, dehumanization, genocide, attack/defense, hate speech), which are debiased and aggregated into a continuous hate speech severity score (hate_speech_score) that includes a region for counterspeech & supportive speeech. Includes 8 target identity groups (race/ethnicity, religion, national origin/citizenship, gender, sexual orientation, age, disability, political ideology) and 42 identity subgroups.

Details of task: Hate speech measurement on social media in English

Size of dataset: 39,565 comments annotated by 7,912 annotators on 10 ordinal labels, for 1,355,560 total labels.

Percentage abusive: 25

Language: English

Level of annotation: Social media comment

Platform: Twitter, Reddit, Youtube

Medium: Text

Reference: Kennedy, C. J., Bacon, G., Sahn, A., & von Vacano, C. (2020). Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application. arXiv preprint arXiv:2009.10277.