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:
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    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
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  - name: total_words
    dtype: int64
  - name: page_text
    dtype: string
  - name: label
    dtype: string
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  - name: test
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- config_name: unbalanced
  features:
  - name: page_title
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  - name: creation_date
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  - name: creator_name
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  - name: total_edits
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  - name: total_editors
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  - name: top_editors
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  - name: bots_editors_percentage
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  - name: humans_editors_percentage
    dtype: float64
  - name: total_bytes
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  - name: total_chars
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  - name: total_words
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  - name: page_text
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  - name: label
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  - name: test
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- 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
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  - name: test
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    num_examples: 113853
  download_size: 141377798
  dataset_size: 759367630
source_datasets:
  - Egyptian Wikipedia
tags:   
- Wikipedia
---
<center><h1> Detect Egyptian Wikipedia <i>Template-translated</i> Articles </h1></center>

## 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:
This Egyptian Arabic Wikipedia articles dataset was extracted from the complete [Wikipedia dumps](https://dumps.wikimedia.org/backup-index.html) of the Egyptian Arabic Wikipedia edition, downloaded on the 1st of January 2024, and processed using the [Gensim](https://radimrehurek.com/gensim/) Python library.

## Dataset Features:
We utilized the Wikimedia [XTools API](https://www.mediawiki.org/wiki/XTools) to collect the Egyptian Arabic Wikipedia articles’ metadata (dataset features). Specifically, we collected the follwoing metadata/features: **total edits**, **total editors**, **top editors**, **total bytes**, **total characters**, **total words**, **creator name**, and **creation date** for each article. 

## 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}
      }
```