Update README.md

README.md

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----
-license: mit
----
+---
+language: 
+  - ar
+tags:
+  - multi label text-classification
+  - arabic
+  - app-reviews
+  - nlp
+dataset_info:
+  features:
+    - name: review
+      dtype: string
+    - name: appName
+      dtype: string
+    - name: platform
+      dtype: string
+    - name: judg_one
+      dtype: string
+    - name: judg_one
+      dtype: string
+    - name: judg_two
+      dtype: string
+    - name: judg_three
+      dtype: string
+    - name: judg_four
+      dtype: string
+    - name: judg_five
+      dtype: string
+  splits:
+    - name: full_dataset
+      num_examples: 2900
+license: mit
+---
+
+# AURA-Classification (Multi-Label Version)
+
+## 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 designed for multi-label text classification, where each review can belong to multiple classes simultaneously.
+Each review in the dataset was independently annotated by five different annotators. To construct the multi-label version of the dataset, a review is assigned to a given class if at least one annotator labeled it with that class. As a result, a single review may be associated with up to four labels.
+
+### 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.
+
+- **judg_one, judg_two, judg_three, judg_four, judg_five**: The labels assigned by each of the five annotators.
+
+The possible classification labels are:
+
+  - `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**: Four possible classes in a multi-label setting (each review may have multiple labels).
+
+### Example Entry
+
+```json
+{
+  "review": "الرجاء تحديث التطبيق لانه اذا سويت البلاغ في النهاية يخرج من الطبيق ولا يتم 
+إرسال البلاغ",
+  "platform": "android",
+  "appname": "تقديم بلاغ مخالفة تجارية",
+  "judg_one": "bug_report",
+  "judg_two": "improvement_request",
+  "judg_three": "bug_report",
+  "judg_four": "improvement_request",
+  "judg_five": "bug_report"
+}
+```
+
+## Use Cases
+
+This dataset is suitable for:
+
+- Multi-label text classification of app reviews.
+
+- Issue identification and requirements elicitation.
+
+- 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)},
+  volume={24},
+  number={2},
+  pages={1--28},
+  year={2025},
+  publisher={ACM New York, NY, USA},
+}
+
+@article{alansari2025multilabel,
+  title   = {Multi-Label Classification of Arabic App Reviews with Data Augmentation and Explainable AI},
+  author  = {Alansari, Aisha and Alomari, Dorieh and Mahmood, Sajjad and Ahmad, Irfan},
+  journal = {Arabian Journal for Science and Engineering},
+  year    = {to-appear},
+  publisher = {Springer}
+}
+```
+
+## 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).