Sentiment Analyzer for Product Reviews

A full-stack web application that analyzes the sentiment of user-submitted reviews or comments (e.g., from Amazon or Twitter) and classifies them as Positive, Neutral, or Negative. Built using Python (Flask) for the backend and React for the frontend.

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Features

• Train and save a logistic regression model using scikit-learn
• REST API built with Flask to serve real-time predictions
• React frontend for user input and displaying sentiment results
• CORS-enabled communication between frontend and backend

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Tech Stack

• Frontend: React, Axios
• Backend: Python, Flask, scikit-learn, joblib, Flask-CORS
• Model: Logistic Regression with TF-IDF vectorizer
• Tools: Postman (for API testing), VS Code (for dev)

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Project Structure

sentiment-analyzer/
├── backend/
│   ├── app.py                  # Flask app with /predict API
│   ├── model/
│   │   ├── train_model.py      # Model training script
│   │   ├── sentiment_model.pkl # Saved ML model
│   │   └── sentiment_data.csv  # CSV with labeled text data
│   └── requirements.txt        # Python dependencies
├── frontend/
│   └── sentiment-ui/           # React app
└── README.md

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Setup Instructions

1. Backend (Flask API)

cd backend
python -m venv venv
source venv/bin/activate      # On Windows: venv\Scripts\activate
pip install -r requirements.txt
cd model
python train_model.py         # Trains and saves model
cd ..
python app.py                 # Starts Flask server at http://127.0.0.1:5000

2. Frontend (React App)

cd frontend
npx create-react-app sentiment-ui
cd sentiment-ui
npm install axios
npm start                     # Starts frontend at http://localhost:3000

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Example Usage

1. Open the app at http://localhost:3000
2. Enter a review like:
   "This is the best product I’ve ever used!"
3. Click "Analyze Sentiment"
4. Output:
   Sentiment: POSITIVE

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Future Enhancements

• Upgrade to Hugging Face Transformers (DistilBERT) for better accuracy
• Add charts for sentiment analysis stats
• Enable batch predictions
• Dockerize and deploy to Render or Railway
• Add CI/CD with GitHub Actions

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License

This project is open-source and free to use under the MIT license.