Mansour-Essgaer/Libyan-Resturant
Domaine:
natural language processingType de record:
dataset
Créateur:
Man
Hôte:
Libyan Restaurants: A Benchmark Dataset for Sentiment Analysis in the Libyan Arabic Dialect
# Libyan Restaurants
### A Benchmark Dataset for Sentiment Analysis in the Libyan Arabic Dialect
## 📌 Overview
The **Libyan Restaurants (LR)** is a manually annotated sentiment analysis dataset written in the Libyan Arabic dialect. The data was collected from real-world restaurant reviews on **Facebook** and **Google Maps**.
The dataset is intended to serve as a benchmark resource for evaluating machine learning and deep learning models in **low-resource Arabic dialect NLP**. This repository provides the dataset, annotation details, and baseline results to ensure reproducibility and fair comparison across studies.
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## 📊 Dataset Statistics
| Attribute | Value |
| :--- | :--- |
| **Total comments** | **4,609** |
| **Positive reviews** | 2,509 (55.4%) |
| **Negative reviews** | 2,020 (44.6%) |
| **Language** | Libyan Arabic dialect |
| **Domain** | Restaurant reviews |
| **Sources** | Facebook, Google Maps |
| **Annotation** | Manual (3 annotators) |
| **Labels** | Binary (1 = Positive, 0 = Negative) |
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## 📁 Data Format
The dataset is provided in **Excel format** with the following structure:
* **`message`**: User comment written in Libyan Arabic.
* **`label`**: Sentiment label (**1** = Positive, **0** = Negative).
### Example Data
```Excel
message,label
"المطعم باهي والخدمة سريعة",1
"الخدمة بلهون بكل والطلب تأخر",0
```
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## 🧾 Annotation Process
To ensure high linguistic validity and contextual accuracy, the following procedure was used:
* **Filtration:** Comments were filtered to retain only Libyan dialect text.
* **Labeling:** Two native Libyan annotators independently labeled each comment.
* **Polarity:** Labels reflect overall sentiment polarity.
* **Exclusions:** Neutral, spam, and non-opinion comments were excluded.
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## 🧪 Benchmark Results (Baseline)
Baseline experiments were conducted using **TF–IDF features** and classical machine learning models. These results are provided as reference baselines for future research.
| Model | Accuracy …