Covers multiple aspects of the issue. Each post in the dataset is annotated from three different perspectives: the basic, commonly used 3-class classification (i.e., hate, offensive or normal), the target community (i.e., the community that has been the victim of hate speech/offensive speech in the post), and the rationales, i.e., the portions of the post on which their labelling decision (as hate, offensive or normal) is based.
Source: HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection
Variants: HateXplain
This dataset is used in 2 benchmarks:
Recent papers with results on this dataset: