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README.md
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language:
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- ko
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pretty_name: K-Haters
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---
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<!--
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### Dataset summary
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We introduces **K-HATERS**, a new corpus for hate speech detection in Korean, comprising approximately 192K news comments with target-specific offensiveness ratings.
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The corpus consists of 192,158 news comments consisting of 183,791 news comments collected by ourselves and 8,367 comments collected from a [previous study](https://aclanthology.org/2020.socialnlp-1.4/).
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- Binary classifiction (labels: normal, toxic(offensive, L1_hate, L2_hate))
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- Rationale prediction (offensiveness, target rationale)
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### Languages
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- Korean
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### Data describtion
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```
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data['train'][42]
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### Labeling guidelines
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Labeling guidelines are available as a part of SELECTSTAR open datasets (in Korean). [link](https://open.selectstar.ai/ko/?page_id=5948)
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### Curation Rationale
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We collected the raw data from the news aggregator of Naver, the largest news portal in Korea. We targeted news articles published in the society, world news, and politics sections because discussions are active in the hard news.
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### Speaker Demographic
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The user demographic is not available. However, considering that the portal site has the largest share of Korean, it can be assumed that speakers are mostly Korean.
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### Text Characteristics
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It includes hatred words limited to Korea, such as hatred of certain political orientations and certain groups. For example, '대깨문' (a word that hates former Korean president Moon's supporter), and '꼴페미' (a word that hates feminists)
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### Licensing information
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This dataset is shared under CC-BY 4.0.
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### Citation information
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```
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- Kyubyong Park (TUNiB)
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- Kunwoo Park
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language:
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- ko
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pretty_name: K-Haters
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tags:
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- hate speech detection
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---
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<!--
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# ℹ️ Dataset card for K-HATERS
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### Dataset summary
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We introduces **K-HATERS**, a new corpus for hate speech detection in Korean, comprising approximately 192K news comments with target-specific offensiveness ratings.
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The corpus consists of 192,158 news comments consisting of 183,791 news comments collected by ourselves and 8,367 comments collected from a [previous study](https://aclanthology.org/2020.socialnlp-1.4/).
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- Binary classifiction (labels: normal, toxic(offensive, L1_hate, L2_hate))
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- Rationale prediction (offensiveness, target rationale)
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### Data describtion
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```
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data['train'][42]
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### Labeling guidelines
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Labeling guidelines are available as a part of SELECTSTAR open datasets (in Korean). [link](https://open.selectstar.ai/ko/?page_id=5948)
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</br>
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# 📜 Data statement
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We present the data statement for responsible usage [(Bender and Friedman, 2018)](https://aclanthology.org/Q18-1041/).
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### Curation Rationale
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We collected the raw data from the news aggregator of Naver, the largest news portal in Korea. We targeted news articles published in the society, world news, and politics sections because discussions are active in the hard news.
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### Language Variety
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Our dataset consists of the news comments in Korean (ko-KR).
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### Speaker Demographic
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The user demographic is not available. However, considering that the portal site has the largest share of Korean, it can be assumed that speakers are mostly Korean.
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### Text Characteristics
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It includes hatred words limited to Korea, such as hatred of certain political orientations and certain groups. For example, '대깨문' (a word that hates former Korean president Moon's supporter), and '꼴페미' (a word that hates feminists)
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</br>
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# 🤝 License & Contributors
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### Licensing information
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This dataset is shared under CC-BY 4.0.
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</br>According to this license, you are free to use the dataset as long as you provide appropriate attribution (e.g., citing our paper).
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### Citation information
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```
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- Kyubyong Park (TUNiB)
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- Kunwoo Park
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#-->
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