---
language:
- ar
license: mit
task_categories:
- text-classification
task_ids:
- sentiment-analysis
tags:
- arabic
- sentiment
- hotel-reviews
- nlp
- arabert
pretty_name: AraReview — Arabic Hotel Reviews Sentiment Dataset
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype: string
  - name: rating
    dtype: int64
  splits:
  - name: train
    num_bytes: 22458814
    num_examples: 84372
  - name: validation
    num_bytes: 2807484
    num_examples: 10547
  - name: test
    num_bytes: 2807484
    num_examples: 10547
  download_size: 12762557
  dataset_size: 28073782
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

# 🏨 AraReview — Arabic Hotel Reviews Sentiment Dataset

A clean, balanced Arabic sentiment analysis dataset built from the HARD (Hotel Arabic Reviews Dataset). Contains **105,466 labeled Arabic hotel reviews** ready for fine-tuning Arabic NLP models like AraBERT, CAMeLBERT, and AraELECTRA.

## Dataset Summary

| Property | Value |
|---|---|
| Language | Arabic (ar) |
| Size | 105,466  reviews |
| Classes | 2 (positive, negative) |
| Class balance | Perfectly balanced, 52,733 per class |
| Source | HARD Hotel Arabic Reviews Dataset    [![GitHub](https://img.shields.io/badge/GitHub-HARDArabicDataset-black)](https://github.com/elnagara/HARD-Arabic-Dataset) |
| Task | Sentiment Classification |

## Class Distribution

| Label | Count | Rating Range |
|---|---|---|
| positive | 52,733 | 4–5 stars |
| negative | 52,733 | 1–2 stars |

## Dataset Structure

### Data Fields

- `text` — cleaned Arabic review text
- `label` — sentiment label (`positive` or `negative`)
- `rating` — original star rating (1, 2, 4, or 5)

### Data Sample

| text | label | rating |
|---|---|---|
| اسوا فندق في العالم. لايوجد اي شي مميز. الفندق قديم... | negative | 1 |
| فندق رائع وخدمه ممتازه. الموقع مميز جدا والغرف نظيفه... | positive | 5 |
| افشل فندق. فاشل بكل المقاييس | negative | 1 |

## Data Pipeline

The dataset was built with a full cleaning pipeline:

**1. Label mapping**
- 1–2 stars → `negative`
- 4–5 stars → `positive`
- Rating 3 not present in source data

**2. Arabic text normalization**
- Removed diacritics (tashkeel / حركات)
- Normalized Alef variants (إ أ آ → ا)
- Normalized Teh Marbuta (ة → ه)
- Normalized Yeh variants (ى → ي)
- Removed English characters
- Removed URLs and HTML tags
- Removed non-Arabic characters and special symbols
- Normalized whitespace

**3. Balancing**
- Undersampled majority class to match minority class
- 52,733 samples per class via random sampling (seed=42)
- Removed reviews shorter than 10 characters after cleaning

## Source Data

Built from the **HARD — Hotel Arabic Reviews Dataset**:
- Original size: ~105K Arabic hotel reviews
- Source: [arbml/HARD](https://huggingface.co/datasets/arbml/HARD)
- Domain: Arabic hotel reviews from booking platforms

## Intended Use

This dataset is intended for:
- Fine-tuning Arabic language models for sentiment analysis
- Benchmarking Arabic NLP models
- Research in Arabic natural language processing

**Models that work well with this dataset:**
- `aubmindlab/bert-base-arabertv2`
- `CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment`
- `aubmindlab/araelectra-base-discriminator`

## How to Use

```python
from datasets import load_dataset

dataset = load_dataset("dralsarrani/AraReview")
print(dataset)
```

```python
# Fine-tuning example
from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("aubmindlab/bert-base-arabertv2")

def tokenize(batch):
    return tokenizer(batch["text"], truncation=True, padding=True, max_length=128)

tokenized = dataset.map(tokenize, batched=True)
```

## Limitations

- Domain-specific: trained on hotel reviews — may not generalize to other Arabic domains without fine-tuning
- Dialect mix: contains Modern Standard Arabic (MSA) and various Arabic dialects
- Binary only: neutral class not included due to absence of 3-star ratings in source data
- Reviews may contain mixed Arabic/English text that was removed during cleaning

## Author

**Danah Al-Sarrani**
AI Engineer

[![GitHub](https://img.shields.io/badge/GitHub-dralsarrani-black)](https://github.com/dralsarrani)
[![HuggingFace](https://img.shields.io/badge/🤗-dralsarrani-yellow)](https://huggingface.co/dralsarrani)