README.md

---
language:
- ar
license: mit
size_categories:
- 100K<n<1M
task_categories:
- text-classification
pretty_name: Detect-Egyptian-Wikipedia-Articles
configs:
- config_name: balanced
  data_files:
  - split: train
    path: balanced/train-*
  - split: test
    path: balanced/test-*
- config_name: unbalanced
  data_files:
  - split: train
    path: unbalanced/train-*
  - split: test
    path: unbalanced/test-*
- config_name: uncategorized
  data_files:
  - split: train
    path: uncategorized/train-*
  - split: test
    path: uncategorized/test-*
dataset_info:
- config_name: balanced
  features:
  - name: page_title
    dtype: string
  - name: creation_date
    dtype: string
  - name: creator_name
    dtype: string
  - name: total_edits
    dtype: int64
  - name: total_editors
    dtype: int64
  - name: top_editors
    dtype: string
  - name: bots_editors_percentage
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  - name: humans_editors_percentage
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  - name: total_bytes
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  - name: total_chars
    dtype: int64
  - name: total_words
    dtype: int64
  - name: page_text
    dtype: string
  - name: label
    dtype: string
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    num_bytes: 32565713
    num_examples: 16000
  - name: test
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    num_examples: 4000
  download_size: 18217654
  dataset_size: 40808941
- config_name: unbalanced
  features:
  - name: page_title
    dtype: string
  - name: creation_date
    dtype: string
  - name: creator_name
    dtype: string
  - name: total_edits
    dtype: int64
  - name: total_editors
    dtype: int64
  - name: top_editors
    dtype: string
  - name: bots_editors_percentage
    dtype: float64
  - name: humans_editors_percentage
    dtype: float64
  - name: total_bytes
    dtype: int64
  - name: total_chars
    dtype: int64
  - name: total_words
    dtype: int64
  - name: page_text
    dtype: string
  - name: label
    dtype: string
  splits:
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    num_examples: 133120
  - name: test
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    num_examples: 33281
  download_size: 59449711
  dataset_size: 165801716
- config_name: uncategorized
  features:
  - name: page_title
    dtype: string
  - name: creation_date
    dtype: string
  - name: creator_name
    dtype: string
  - name: total_edits
    dtype: int64
  - name: total_editors
    dtype: int64
  - name: top_editors
    dtype: string
  - name: bots_editors_percentage
    dtype: float64
  - name: humans_editors_percentage
    dtype: float64
  - name: total_bytes
    dtype: int64
  - name: total_chars
    dtype: int64
  - name: total_words
    dtype: int64
  - name: page_text
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 607754601
    num_examples: 455411
  - name: test
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    num_examples: 113853
  download_size: 141377798
  dataset_size: 759367630
source_datasets:
  - Egyptian Wikipedia
tags:   
- Wikipedia
---
# Detect Egyptian Wikipedia *Template-translated* Articles:

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 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:
### 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**. *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}
}