faiz-oussama/darija-sentiments-analysis-webapp

# 🔍 Darija Sentiment Analysis A modern web application for sentiment analysis of Darija (Moroccan Arabic dialect) text. Analyze sentiment in Darija text with state-of-the-art machine learning --- ## 📋 Table of Contents - Project Overview - Features - Project Structure - Getting Started - Prerequisites - Installation - Running the Application - Usage - Model Information - Technologies Used - Contributing - License - Acknowledgments --- ## 🌟 Project Overview This project provides a sentiment analysis tool that can determine whether a given text in Darija has a positive, negative, or neutral sentiment. It consists of three main components: - **ML Model**: A trained BERT-based sentiment analysis model specialized for Darija text - **Flask API**: Backend service that handles text processing and sentiment prediction - **Next.js Frontend**: Modern, responsive web interface for user interaction --- ## ✨ Features - ⚡ Real-time sentiment analysis of Darija text - 📊 Visual representation of sentiment scores - 📱 Responsive design for desktop and mobile devices - 🌙 Dark theme with a modern interface --- ## 📂 Project Structure ```bash Darija-Sentiment-Analysis/ ├── datasets/ # Training and testing datasets ├── flask-api/ # Flask backend API service ├── front-end/ # Next.js frontend application ├── model-training-notebook/# Jupyter notebooks for model training └── darija_sentiment_model.pt # Trained sentiment analysis model ``` --- ## 🚀 Getting Started ### Prerequisites - Python 3.8+ (for backend) - Node.js 18+ (for frontend) - pip (Python package manager) - npm (Node.js package manager) ### Installation 1. Clone the repository: ```bash git clone github.com cd Darija-Sentiment-Analysis ``` 2. Set up the Flask API: ```bash cd flask-api pip install -r requirements.txt # Required packages: flask, flask-cors, torch, numpy, transformers ``` 3. Set up the Next.js fron …