File size: 5,772 Bytes
aafcf70 d35a703 aafcf70 4865626 d35a703 aafcf70 4865626 aafcf70 4865626 d35a703 8a9c7e0 4b4cbd9 aafcf70 ac233c7 1e03964 6ce55f0 6445b65 a79f3f2 f217a5e a1a2f92 6ce55f0 817e5ba d1403a4 391789c 53ff71b 6a0e83a eef92ec a931e12 391789c eef92ec a1a2f92 d1403a4 17ee4b3 6ce55f0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 |
---
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 *Template-translated* 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:
## 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}
}
```
|