---
title: x_sensitive
canonical_url: "https://www.modelscope.cn/datasets/cardiffnlp/x_sensitive"
md_url: "https://www.modelscope.cn/datasets/cardiffnlp/x_sensitive.md"
repository: cardiffnlp/x_sensitive
last_updated: 2025-10-12
license: cc-by-2.0
storage_size: "29 MB"
downloads: 87
stars: 0
---

# x_sensitive

> x_sensitive - cardiffnlp 在 ModelScope 开源的数据集。X-Sensitive is a multi-label dataset designed to identify sensitive language in social media. It consists of 7 labels and includes a total of 8,000 posts extracted from X. Each post is assigned one or more of the…

cardiffnlp/x_sensitive 是 ModelScope 魔搭社区上的数据集，存储大小 29 MB，采用 cc-by-2.0 许可。

- **Repository**: cardiffnlp/x_sensitive
- **License**: cc-by-2.0
- **Storage size**: 29 MB
- **Downloads**: 87
- **Stars**: 0
- **Last updated**: 2025-10-12

Source: https://www.modelscope.cn/datasets/cardiffnlp/x_sensitive

---

***X-Sensitive*** is a multi-label dataset designed to identify sensitive language in social media. 
It consists of 7 labels and includes a total of 8,000 posts extracted from ***X***. 
Each post is assigned one or more of the following labels based on its content: ***Drugs, Sex, Conflictual, Spam, Profanity, and Self-harm***. 
More details in the [reference paper](https://arxiv.org/abs/2411.19832).

The goal of ***X-Sensitive*** is to serve as a valuable resource for developing online moderation tools. The following models have been trained on ***X-Sensitive*** with this aim:

- [twitter-roberta-large-sensitive-multilabel](https://huggingface.co/cardiffnlp/twitter-roberta-large-sensitive-multilabel)
- [twitter-roberta-base-sensitive-multilabel](https://huggingface.co/cardiffnlp/twitter-roberta-base-sensitive-multilabel)

We also provide binary versions of the models, where each post is classified as either sensitive or not-sensitive:

- [twitter-roberta-large-sensitive-binary](https://huggingface.co/cardiffnlp/twitter-roberta-large-sensitive-binary)
- [twitter-roberta-base-sensitive-binary](https://huggingface.co/cardiffnlp/twitter-roberta-base-sensitive-binary)

## Dataset Structure

### Data Splits

| Name | #Entries    |
|--------------|---------------|
| ***train*** | 5,000    |
| ***test*** | 2,000    |
| ***validation*** | 1,000    |

### Data Instances
An example of `train` looks as follows.

```python
{'#labels': 1,
 'conflictual': 0,
 'conflictual_highlight': array([], dtype=object),
 'drugs': 0,
 'drugs_highlight': array([], dtype=object),
 'keyword': 'fuckin',
 'labels': array(['profanity'], dtype=object),
 'profanity': 1,
 'profanity_highlight': array([array(['fucking'], dtype=object), array(['fucking'], dtype=object),
       array(['fucking'], dtype=object)], dtype=object),
 'selfharm': 0,
 'selfharm_highlight': array([], dtype=object),
 'sex': 0,
 'sex_highlight': array([], dtype=object),
 'spam': 0,
 'spam_highlight': array([], dtype=object),
 'text': 'i think the idea of aliens is so fucking cool'}
```

### Labels
| Label Number | Label Name    | Description
|--------------|---------------|---------------|
| 0            | conflictual   | Conflictual language. An attack based on protected (race, color, caster, gender, etc) or other categories.|
| 1            | profanity     | Language containing slurs and profanity even if they are not directed towards a specific entity.|
| 2            | sex           | Sexually Explicit Content. Pornographic or other types of sexual content. 
| 4            | selfharm      | Self-harm. Posts depicting, promoting, or glorifying violence or harm against oneself such as eating disorders or suicide.
| 5            | spam          | Irrelevant content that is unsolicited.




## Citation Information
```
@article{antypas2024sensitive,
  title={Sensitive Content Classification in Social Media: A Holistic Resource and Evaluation},
  author={Antypas, Dimosthenis and Sen, Indira and Perez-Almendros, Carla and Camacho-Collados, Jose and Barbieri, Francesco},
  journal={arXiv preprint arXiv:2411.19832},
  year={2024}
}
```