--- annotations_creators: - crowdsourced - crowd-generated language_creators: - found language: - ko license: - cc-by-sa-4.0 multilinguality: - monolingual paperswithcode_id: apeach pretty_name: 'APEACH' size_categories: - 1Kbase ## Dataset Descritpion Korean Hate Speech Evaluation Datasets : trained with [BEEP!](https://huggingface.co/datasets/kor_hate) and evaluate with [APEACH](https://github.com/jason9693/APEACH) - **Repository: [Korean HateSpeech Evaluation Dataset](https://github.com/jason9693/APEACH)** - **Paper: [APEACH: Attacking Pejorative Expressions with Analysis on Crowd-Generated Hate Speech Evaluation Datasets](https://arxiv.org/abs/2202.12459)** - **Point of Contact: [Kichang Yang](ykcha9@gmail.com)** ### Languages ko-KR ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json {'text': ['(현재 호텔주인 심정) 아18 난 마른하늘에 날벼락맞고 호텔망하게생겼는데 누군 계속 추모받네....', '....한국적인 미인의 대표적인 분...너무나 곱고아름다운모습...그모습뒤의 슬픔을 미처 알지못했네요ㅠ'], 'class': ['Spoiled', 'Default']} ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "text": "Value(dtype='string', id=None)", "class": "ClassLabel(num_classes=2, names=['Default', 'Spoiled'], id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train (binarized BEEP!) | 7896 | | valid (APEACH) | 3770 | ## Citation ``` @article{yang2022apeach, title={APEACH: Attacking Pejorative Expressions with Analysis on Crowd-Generated Hate Speech Evaluation Datasets}, author={Yang, Kichang and Jang, Wonjun and Cho, Won Ik}, journal={arXiv preprint arXiv:2202.12459}, year={2022} } ```