---
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
    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: 32565713
    num_examples: 16000
  - name: test
    num_bytes: 8243228
    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:
  - name: train
    num_bytes: 132509046
    num_examples: 133120
  - name: test
    num_bytes: 33292670
    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
    num_bytes: 151613029
    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://aclanthology.org/2024.osact-1.4/)", 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 metadata (dataset features) of the Egyptian Arabic Wikipedia articles. Specifically, we collected the following metadata/features for each article: **total edits**, **total editors**, **top editors**, **total bytes**, **total characters**, **total words**, **creator name**, and **creation date**. 

## 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. 

## Dataset Citations:
<s>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*.</s>

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://aclanthology.org/2024.osact-1.4/). *In Proceedings of the 6th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT) with Shared Tasks on Arabic LLMs Hallucination and Dialect to MSA Machine Translation @ LREC-COLING 2024*, pages 31–45, Torino, Italia. ELRA and ICCL.*