File size: 1,720 Bytes
7f7ac5c 7688a68 7f7ac5c 7688a68 7f7ac5c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | # HateXplain: Annotated Dataset for Hate Speech and Offensive Language Explanation
**HateXplain** is a benchmark dataset for hate speech and offensive language detection, uniquely annotated with *explanations* and *rationales*. It is designed to support the development of interpretable models in online content moderation.
---
## 📚 Dataset Summary
- **Languages**: English
- **Samples**: ~20,000 social media posts
- **Annotations**:
- `label`: `normal`, `offensive`, or `hatespeech`
- `annotators`: Multiple annotators per post with consensus labeling
- `rationales`: Token-level binary rationales indicating why the label was chosen
---
## 📁 Dataset Structure
| Column | Description |
|---------------|---------------------------------------------------------------------------|
| `post_id` | Unique ID for each post (e.g., Twitter ID) |
| `post_tokens` | List of tokenized words from the post |
| `annotators` | List of dictionaries with label, annotator_id, and rationale |
| `rationales` | List of lists indicating which tokens are part of the explanation |
---
## 🔍 Example Entry
```json
{
"post_id": "1179055004553900032_twitter",
"post_tokens": ["i", "dont", "think", "im", "getting", "my", "baby", "them", "white", "9", "s", "for", "school"],
"annotators": [
{
"label": "normal",
"annotator_id": 1,
"rationale": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
}
],
"rationales": []
}
|