| --- |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| tags: |
| - text-moderation |
| language: |
| - en |
| - de |
| - fr |
| - es |
| - it |
| - sv |
| - fi |
| - pl |
| - cs |
| - lv |
| - zh |
| - ja |
| - ko |
| - ru |
| - uk |
| - be |
| - kk |
| --- |
| |
| # Text-Moderation-Multilingual |
|
|
| A comprehensive multilingual text moderation dataset combining multiple high-quality sources for training robust content moderation classifiers. |
|
|
| ## Dataset Summary |
|
|
| This dataset aggregates text moderation data from multiple sources to create a large-scale, diverse training corpus for content moderation systems. It includes text samples labeled across multiple harmful content categories, supporting both multilingual and English-specific moderation use cases. |
|
|
| **Total Size:** ~1.7M entries |
| **Languages:** Multilingual (primary focus on English) |
| **Task:** Multi-label text classification for content moderation |
|
|
| ## Dataset Structure |
|
|
| ### Data Fields |
|
|
| - `prompt` (string): The input text to be classified |
| - `S` (int): Sexual content (0 = safe, 1 = harmful) |
| - `H` (int): Hate speech (0 = safe, 1 = harmful) |
| - `V` (int): Violence (0 = safe, 1 = harmful) |
| - `HR` (int): Harassment (0 = safe, 1 = harmful) |
| - `SH` (int): Self-harm (0 = safe, 1 = harmful) |
| - `S3` (int): Sexual content involving minors (0 = safe, 1 = harmful) |
| - `H2` (int): Hate speech (alternative labeling) (0 = safe, 1 = harmful) |
| - `V2` (int): Violence (alternative labeling) (0 = safe, 1 = harmful) |
|
|
| ### Data Splits |
|
|
| - **Train:** 1459350 samples |
| - **Validation:** 162150 samples |
|
|
| *Note: Split created with 90/10 train/validation ratio using random seed 42* |
|
|
| ## Source Datasets |
|
|
| This dataset combines and harmonizes data from: |
|
|
| - **[ifmain's multilingual dataset](https://huggingface.co/datasets/ifmain/text-moderation-02-multilingual)** - Multilingual moderation examples |
| - **[OpenAI's English evaluation dataset](https://huggingface.co/datasets/mmathys/openai-moderation-api-evaluation)** - High-quality English evaluation samples |
| - **[ifmain's English dataset](https://huggingface.co/datasets/ifmain/text-moderation-01)** - English moderation examples |
|
|
| ## Intended Use |
|
|
| ### Primary Use Cases |
| - Training text moderation classifiers |
| - Benchmarking content moderation systems |
| - Research into automated content moderation |
| - Multi-label classification model development |
|
|
| ### Out-of-Scope Uses |
| - This dataset is **not intended** for any purpose other than training content moderation systems |
| - Should not be used to generate harmful content |
| - Not suitable for general text classification tasks outside of moderation |
|
|
| ## Considerations for Using the Data |
|
|
| ### Content Warning |
| This dataset contains examples of harmful content including hate speech, harassment, violence, and other potentially disturbing material. Users should exercise appropriate caution when working with this data. |
|
|
| ### Bias and Limitations |
| - The dataset reflects the biases present in the source datasets |
| - Content moderation standards may vary across different platforms and cultures |
| - Label consistency across merged datasets may vary |
| - Primarily English-focused despite multilingual components |
|
|
| ### Ethical Considerations |
| - This dataset should only be used to improve content moderation and safety systems |
| - Researchers and developers should implement appropriate safeguards when working with this data |
| - The goal is to reduce harmful content online, not to amplify it |
|
|
| ## Example Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load the dataset |
| dataset = load_dataset("KoalaAI/Text-Moderation-Multilingual") |
| |
| # Access splits |
| train_data = dataset["train"] |
| val_data = dataset["validation"] |
| |
| # Example entry |
| print(train_data[0]) |
| # { |
| # 'prompt': 'Example text...', |
| # 'S': 0, 'H': 0, 'V': 0, 'HR': 0, |
| # 'SH': 0, 'S3': 0, 'H2': 0, 'V2': 0 |
| # } |
| ``` |
|
|
| ## Dataset Creation |
|
|
| ### Curation Process |
| 1. Source datasets were identified and downloaded |
| 2. Data was harmonized to use consistent labeling schema |
| 3. Entries were merged and deduplicated where appropriate |
| 4. Train/validation split was created using stratified sampling |
|
|
| ### Quality Control |
| - Labels were preserved from original high-quality sources |
| - Data integrity checks were performed during merging process |
| - Consistent schema applied across all entries |
|
|
| ## License |
|
|
| Please refer to the licenses of the individual source datasets: |
| - Check ifmain datasets for their respective licensing terms |
| - OpenAI evaluation dataset licensing applies to that portion |
| - Usage should comply with all source dataset requirements |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the original source datasets: |
|
|
| ```bibtex |
| @misc{text-moderation-large, |
| title={Text-Moderation-Multilingual: A Multilingual Text Moderation Dataset}, |
| author={[KoalaAI]}, |
| year={2025}, |
| note={Aggregated from ifmain's and OpenAI's moderation datasets} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| For questions about this dataset compilation, please open an issue on this repository. |
|
|
| --- |
|
|
| **Disclaimer:** This dataset is provided for research and safety purposes only. Users are responsible for ensuring ethical use and compliance with applicable laws and regulations. |
