APEACH: Attacking Pejorative Expressions with Analysis on Crowd-generated Hate Speech Evaluation Datasets

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Text Data & NLPAPEACH
Overview

APEACH - Korean Hate Speech Evaluation Datasets

APEACH is the first crowd-generated Korean evaluation dataset for hate speech detection. Sentences of the dataset are created by anonymous participants using an online crowdsourcing platform DeepNatural AI.

  • Sample Code : base

Download

You can download benchmark set APEACH. APEACH/test.csv in this repository.

Dataset Description

  • APEACH : A hate-speech evaluation dataset generated in 2021, using generation method followd by APEACH paper.

Guidelines

APEACH-GUIDELINE

Topics

Lengths

Paper

Experiment Code

base

Experiment Results

Name Beep! Dev Dataset Apeach (Ours)
SoongsilBERT-Base 0.8261 0.8424
SoongsilBERT-Small 0.8149 0.8228
KcBERT-base 0.8088 0.8086
KcBERT-large 0.8295 0.8116
DistillKoBERT 0.7570 0.7715
KoELECTRA-V3 0.7920 0.8101
KoBERT 0.8030 0.7885

We also share BEST model of our dataset which we trained in this experiment as checkpoint, demo webite and api.

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}
}

Contributors

The main contributors of the work ( * : equal contribution) :

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Owner
Kevin-Yang
Kevin-Yang
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