---
language: 
  - ar
tags:
  - text-classification
  - arabic
  - app-reviews
  - nlp
dataset_info:
  features:
    - name: review
      dtype: string
    - name: appName
      dtype: string
    - name: platform
      dtype: string
    - name: label
      dtype: string
  splits:
    - name: full_dataset
      num_examples: 2900
license: mit
---

# AURA-Classification

## Dataset Description

The AURA (App User Review in Arabic) Classification dataset is a collection of 2,900 Arabic-language app reviews collected from various mobile applications. This dataset is primarily designed for text classification tasks.

### Features

The dataset includes the following fields:

- **review**: The text of the review in Arabic.

- **appName**: The name of the application being reviewed.

- **platform**: The platform (iOS or Android) where the review was posted.

- **label**: The classification label for the review, categorized as:

  - `bug_report`: The review highlights a bug or issue in the app.
  - `improvement_request`: The review suggests improvements or features.
  - `rating`: The review expresses a general rating or opinion.
  - `others`: Miscellaneous or uncategorized reviews.

### Dataset Statistics

- **Total Reviews**: 2,900
- **Platforms**: iOS, Android
- **Applications**: Multiple apps from diverse categories.
- **Labels Distribution**: The dataset is labeled into four categories for multi-class classification tasks.

### Example Entry

```json
{
  "review": "يبيله تصليحات كثير",
  "appName": "OSN - Streaming App",
  "platform": "ios",
  "label": "bug_report"
}
```

## Use Cases

This dataset is suitable for:

- Text classification (e.g., topic classification, issue identification).

- Multilingual NLP research focused on Arabic.

- Fine-tuning models for app review classification.

## Citation

If you use this dataset, please cite it as:

```
@article{Aljeezani2025arabic,
  title={Arabic App Reviews: Analysis and Classification},
  author={Aljeezani, Othman and  Alomari, Dorieh and Ahmad, Irfan},
  journal={ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)},
  pages={1--28},
  year={to-appear},
  publisher={ACM New York, NY, USA},
}
```

## License

This dataset is shared under the [MIT License](https://opensource.org/licenses/MIT). Please ensure appropriate attribution when using this dataset.

## Acknowledgments

Special thanks to the contributors and reviewers who made this dataset possible.

## Contact

For questions or feedback, please reach out to the corresponding author (Irfan Ahmad).