nomeda-lab/hindawi-arabic-sections

Hindawi Arabic Books — Sections Dataset

A cleaned, section-level dataset of Arabic books from Hindawi.org, prepared for NLP training and research.

Source

Original books scraped from Hindawi.org, a non-profit foundation providing free Arabic books. The dataset covers categories including literature, philosophy, history, science, psychology, and more.

Cleaning Pipeline

1. Scraped book content section-by-section from Hindawi.org
2. Removed English / Latin text and characters
3. Removed tashkeel (Arabic diacritics: َ ُ ِ ْ ّ etc.)
4. Removed tatweel (kashida: ـ)
5. Normalized Arabic letters:
   • أ إ آ ٱ → ا
   • ى → ي
   • ة → ه
6. Deduplicated exact duplicate lines and near-duplicate paragraphs (فرهس)
7. Replaced Eastern Arabic numerals (٠١٢٣٤٥٦٧٨٩ and ۰۱۲۳۴۵۶۷۸۹) with Western 0-9
8. Collapsed each section to a single line (newlines → spaces)
9. Filtered sections with fewer than 250 characters
10. Cross-book deduplication: removed 342 sections that were >95% similar to sections in other books (3,253 duplicate pairs found, mean similarity 99.79%)

Splits

Split	Rows	Percentage
train	47,546	90.0%
validation	2,642	5.0%
test	2,642	5.0%

Split was done with train_test_split from scikit-learn with random_state=42 and shuffle=True.

Columns

Column	Type	Description
text	string	Cleaned Arabic text of the section (single line)
book_title	string	Title of the parent book
author	string	Author name
category	string	Book category (e.g., أدب, فلسفة, تاريخ, علم نفس)
section_title	string	Title of the section within the book
chars	int64	Character count of the section text
book_id	string	Hindawi book ID (when available)

Category Distribution (top 10)

Category	Sections
أدب	10,441
تاريخ	6,383
روايات	6,373
فلسفة	4,424
شعر	3,947
سير الأعلام	2,554
علوم اجتماعية	2,229
علوم	1,916
نقد أدبي	1,903
سياسة	1,723

Usage Example

from datasets import load_dataset

dataset = load_dataset("your-username/hindawi-arabic-sections")

# Access train split
print(dataset["train"][0]["text"][:200])

# Filter by category
history = dataset["train"].filter(lambda x: x["category"] == "تاريخ")

Loading with Pandas

import pandas as pd

train = pd.read_parquet("train.parquet")
print(train.head())

Statistics

Total sections:     52,830
Total books:        3,265
Total characters:   843,868,321
Mean chars/section: 15,973.3
Median chars/section: 7,915.0
Min chars:          250
Max chars:          723,964
Std dev:            ~26,000

Citation

@dataset{hindawi_arabic_sections,
  title = {Hindawi Arabic Books — Sections Dataset},
  year = {2026},
  publisher = {Hindawi Foundation},
  url = {https://www.hindawi.org}
}

License

The original books are made available by Hindawi Foundation under their free-access agreement. This dataset is a derived work prepared for research and educational purposes.

Acknowledgments

• Hindawi Foundation for making these books freely available
• This dataset was prepared using automated scraping and cleaning tools