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The "gender identity" subset of the large-scale dataset published in the LREC 2022 paper "Large-Scale Hate Speech Detection with Cross-Domain Transfer".
This subset is used in the experiments of "Şahinuç, F., Yilmaz, E. H., Toraman, C., & Koç, A. (2023). The effect of gender bias on hate speech detection. Signal, Image and Video Processing, 17(4), 1591-1597."
The "gender identity" subset includes 20,000 tweets in English.
The published data split is the first fold of 10-fold cross-validation, used in the experiments mentioned above.
Train split has 18,000 tweets. Test split has 2,000 tweets.
HateLabel:
- 0 Normal
- 1 Offensive
- 2 Hate
GitHub Repo:
https://github.com/avaapm/hatespeech
If you use this dataset, please cite the following papers:
- Toraman, C., Şahinuç, F., & Yilmaz, E. (2022, June). Large-Scale Hate Speech Detection with Cross-Domain Transfer. In Proceedings of the Thirteenth Language Resources and Evaluation Conference (pp. 2215-2225).
- Şahinuç, F., Yilmaz, E. H., Toraman, C., & Koç, A. (2023). The effect of gender bias on hate speech detection. Signal, Image and Video Processing, 17(4), 1591-1597.
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