VN-HSD / README.md
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---
task_categories:
- text-classification
language:
- vi
---
## Dataset Card for ViSoLex‑HSD
### 1. Dataset Summary
**ViSoLex‑HSD** is a unified Vietnamese hate‐speech detection corpus, combining three benchmark datasets:
* **ViHSD** (Son et al., 2021): 33K comments labeled **CLEAN**, **OFFENSIVE**, or **HATE**
* **UIT‑ViCTSD** (Nguyen et al., 2020): 10K comments annotated for **TOXIC** (mapped to **HATE**) or **CLEAN**
* **ViHOS** (Hoang et al., 2023): span‐level labels aggregated into comment‐level **HATE**/**CLEAN**
After renaming and mapping labels (0 = CLEAN; 1 = OFFENSIVE; 2 = HATE) and concatenating - with duplicate comments removed - the final DataFrame contains:
* **Columns**:
* `dataset`: original source (`ViHSD`/`ViCTSD`/`ViHOS`)
* `type`: split indicator (`train`/`validation`/`test`)
* `comment`: raw text
* `label`: numeric (0/1/2)
### 2. Supported Tasks and Metrics
* **Task**: Text classification – Hate speech detection
* **Labels**:
* 0 → CLEAN (no offensive content)
* 1 → OFFENSIVE (non‐hate offensive language)
* 2 → HATE (hate speech)
* **Metrics**: Accuracy, Precision/Recall/F1 per class
### 3. Languages
* Vietnamese
### 4. Dataset Structure
| Column | Type | Description |
| --------- | ------ | -------------------------------------- |
| `dataset` | string | Origin: `ViHSD` / `ViCTSD` / `ViHOS` |
| `type` | string | Split: `train` / `validation` / `test` |
| `comment` | string | The social‐media comment in Vietnamese |
| `label` | int | 0=CLEAN, 1=OFFENSIVE, 2=HATE |
### 6. Usage
```python
from datasets import load_dataset
ds = load_dataset("your-namespace/visolex-hsd")
train_ds = ds.filter(lambda x: x["type"] == "train")
val_ds = ds.filter(lambda x: x["type"] == "dev")
test_ds = ds.filter(lambda x: x["type"] == "test")
print(train_ds.features)
print(train_ds[0])
```
### 7. Dataset Creation & Processing
1. **Load original CSVs** for ViHSD, ViCTSD, ViHOS.
2. **Rename columns** to `comment` and `label`.
3. **Map labels**:
* ViHSD: keep 0/1/2.
* ViCTSD: map `Toxicity` 1→2, 0→0.
* ViHOS: span‐exists→2, no span→0.
4. **Concatenate**, retain only `dataset`, `type`, `comment`, `label`.
5. **Drop duplicates** on `comment`.
(Refer to the code snippet in the prompt.)
### 8. Source & Links
* **ViHSD**:
* GitHub: [https://github.com/sonlam1102/vihsd](https://github.com/sonlam1102/vihsd)
* Hugging Face: [https://huggingface.co/datasets/sonlam1102/vihsd](https://huggingface.co/datasets/sonlam1102/vihsd)
* Paper: Luu et al. (2021), “A large-scale dataset for hate speech detection on Vietnamese social media texts.”
* **UIT‑ViCTSD**:
* GitHub: https://github.com/tarudesu/ViCTSD
* Hugging Face: [https://huggingface.co/datasets/tarudesu/ViCTSD](https://huggingface.co/datasets/tarudesu/ViCTSD)
* Paper: “Constructive and Toxic Speech Detection for Open-domain Social Media Comments in Vietnamese” (Nguyen et al., 2020).
* **ViHOS**:
* GitHub: [https://github.com/phusroyal/ViHOS](https://github.com/phusroyal/ViHOS)
* Hugging Face: [https://huggingface.co/datasets/phusroyal/ViHOS](https://huggingface.co/datasets/phusroyal/ViHOS)
* Paper: Hoang et al. (2023), “ViHOS: Hate Speech Spans Detection for Vietnamese.”
### 9. Licenses & Citation
Please see each source’s license. If unspecified, assume **MIT** or **CC BY 4.0**.
**Citation Information**:
```bibtex
@inproceedings{luu2021large,
title={A large-scale dataset for hate speech detection on vietnamese social media texts},
author={Luu, Son T and Nguyen, Kiet Van and Nguyen, Ngan Luu-Thuy},
booktitle={Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices: 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26--29, 2021, Proceedings, Part I 34},
pages={415--426},
year={2021},
organization={Springer}
}
```
```bibtex
@InProceedings{nguyen2021victsd,
author="Nguyen, Luan Thanh and Van Nguyen, Kiet and Nguyen, Ngan Luu-Thuy",
title="Constructive and Toxic Speech Detection for Open-Domain Social Media Comments in Vietnamese",
booktitle="Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="572--583"
}
```
```bibtex
@inproceedings{hoang-etal-2023-vihos,
title = "{V}i{HOS}: Hate Speech Spans Detection for {V}ietnamese",
author = "Hoang, Phu Gia and
Luu, Canh Duc and
Tran, Khanh Quoc and
Nguyen, Kiet Van and
Nguyen, Ngan Luu-Thuy",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.47",
doi = "10.18653/v1/2023.eacl-main.47",
pages = "652--669"
}
```
[1]: https://arxiv.org/html/2404.19252v2?utm_source=chatgpt.com "ViTHSD: Exploiting Hatred by Targets for Hate Speech Detection on ..."
[2]: https://paperswithcode.com/dataset/uit-victsd?utm_source=chatgpt.com "UIT-ViCTSD Dataset - Papers With Code"
[3]: https://huggingface.co/datasets/phusroyal/ViHOS "phusroyal/ViHOS · Datasets at Hugging Face"