--- language: - ar license: mit size_categories: - 100K

Detect Egyptian Wikipedia Template-translated Articles

## Dataset Description: We release the heuristically filtered, manually processed, and automatically classified Egyptian Arabic Wikipedia articles dataset. This dataset was used to develop a **web-based detection system** to automatically identify the template-translated articles on the Egyptian Arabic Wikipedia edition. The system is called [**Egyptian Arabic Wikipedia Scanner**](https://egyptian-wikipedia-scanner.streamlit.app/) and is hosted on Hugging Face Spaces, here: [**SaiedAlshahrani/Detect-Egyptian-Wikipedia-Articles**](https://huggingface.co/spaces/SaiedAlshahrani/Egyptian-Wikipedia-Scanner). This dataset is introduced in a research paper titled "[***Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition***](https://arxiv.org/abs/2404.00565)", which is **accepted** at [LREC-COLING 2024](https://lrec-coling-2024.org/): [The 6th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT6)](https://osact-lrec.github.io/), and is currently released under an MIT license. ## Dataset Sources: ## Dataset Features: ## Dataset Subsets: 1. **Balanced**: A balanced subset of the dataset comprised 20K (10K for each class) and was split in the ratio of 80:20 for training and testing. This subset was filtered and processed using selected heuristic rules. 2. **Unbalanced**: An unbalanced subset of the dataset comprised 166K and was split in the ratio of 80:20 for training and testing. This subset is the rest of the filtered and processed articles using selected heuristic rules. 3. **Uncategorized**: Another unbalanced subset of the dataset comprised 569K and was split in the ratio of 80:20 for training and testing, but this was classified automatically using the `XGBoost` classifier trained using the balanced subset. ## Citations: Please cite our paper if you have used our dataset in any way 😊 ### Short Citation: Saied Alshahrani, Hesham Haroon, Ali Elfilali, Mariama Njie, and Jeanna Matthews. 2024. [Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition](https://arxiv.org/abs/2404.00565). *arXiv preprint arXiv:2404.00565*. ### BibTeX Citation: ``` @article{alshahrani2024leveraging, title={Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition}, author={Saied Alshahrani and Hesham Haroon and Ali Elfilali and Mariama Njie and Jeanna Matthews}, year={2024}, eprint={2404.00565}, archivePrefix={arXiv}, primaryClass={cs.CL} journal={arXiv preprint arXiv:2404.00565}, url={https://arxiv.org/abs/2404.00565} } ```