README.md

metadata

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:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - binary-classification

Dataset for project: kor_hate_eval(APEACH)

Sample Code

Dataset Descritpion

Korean Hate Speech Evaluation Datasets : trained with BEEP! and evaluate with APEACH

• Repository: Korean HateSpeech Evaluation Dataset
• Paper: APEACH: Attacking Pejorative Expressions with Analysis on Crowd-Generated Hate Speech Evaluation Datasets
• Point of Contact: Kichang Yang

Languages

ko-KR

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

{'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"):

{
  "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}
}