ElSherief et al. Hate Speech Instigators and Their Targets Dataset from Twitter

Dataset of hate speech and targets from Twitter collected through a multi-step classification process and annotated through CrowdFlower. 92.8% agreement among the annotators for hateful/not and 82.6% agreement for whether targetted at a person. The posts are sampled by different "hate" keywords and hate speech categories.

Data and Resources

Additional Info

Field Value
Authors ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G. and Belding, E.
Author contact email ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G. and Belding, E.
Publication / paper reference ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G. and Belding, E., 2018. Peer to Peer Hate: Hate Speech Instigators and Their Targets. In: Proceedings of the Twelfth International AAAI Conference on Web and Social Media (ICWSM 2018). Santa Barbara, California: University of California, pp.52-61.
Publication / paper link https://aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17905/16996
Dataset about page https://github.com/mayelsherif/hate_speech_icwsm18
Language(s) covered English
Source data platform(s) Twitter
Annotation schema description Binary (Hate/Not)
Phenomena annotated person- & group-directed hate speech
Level of instances Single comment / post
Data statement link N/A
Total umber of instances in dataset 27,330
Proportion of positive/abusive instances 0.98
Submitter Philine Zeinert
Submitter Email phze@itu.dk
State active