Update README.md

README.md

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----
-dataset_info:
-  features:
-  - name: review
-    dtype: string
-  - name: appName
-    dtype: string
-  - name: platform
-    dtype: string
-  - name: label
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 544820
-    num_examples: 2900
-  download_size: 252805
-  dataset_size: 544820
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+# 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{Aljizani2025,
+  title={Arabic App Reviews: Analysis and Classification},
+  author={Aljeezani, Othman and  Alomari, Dorieh and Ahmad, Irfan},
+  journal={ACM Transactions on Asian Language Information Processing (TALIP)},
+  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.
+