Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Korean
Size:
10K - 100K
ArXiv:
License:
File size: 2,348 Bytes
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---
annotations_creators:
- crowdsourced
- crowd-generated
language_creators:
- found
languages:
- ko
licenses:
- 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
## 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": "(\ud604\uc7ac \ud638\ud154\uc8fc\uc778 \uc2ec\uc815) \uc54418 \ub09c \ub9c8\ub978\ud558\ub298\uc5d0 \ub0a0\ubcbc\ub77d\ub9de\uace0 \ud638\ud154\ub9dd\ud558\uac8c\uc0dd\uacbc\ub294\ub370 \ub204\uad70 \uacc4\uc18d \ucd94\ubaa8\ubc1b\ub124....",
"class": 1
},
{
"text": "....\ud55c\uad6d\uc801\uc778 \ubbf8\uc778\uc758 \ub300\ud45c\uc801\uc778 \ubd84...\ub108\ubb34\ub098 \uacf1\uace0\uc544\ub984\ub2e4\uc6b4\ubaa8\uc2b5...\uadf8\ubaa8\uc2b5\ub4a4\uc758 \uc2ac\ud514\uc744 \ubbf8\ucc98 \uc54c\uc9c0\ubabb\ud588\ub124\uc694\u3160",
"class": 0
}
]
```
### 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}
}
```
|