📋 Sentify Reviews

📊 Review Sentiment Analysis and Insights Platform

💡Sentify Reviews is an advanced project designed to analyze customer reviews and deliver actionable insights

Leveraging state-of-the-art Natural Language Processing (NLP) and deep learning techniques, this project classifies review sentiments, identifies potential bot-generated reviews, and extracts contextual insights to help businesses make informed decisions.

It can be used to evaluate product performance, monitor customer feedback, or provide valuable insights to assist with purchase decisions during online shopping. Sentify Reviews is designed to be simple, effective, and user-friendly.

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⭐ Features

1. Basic Sentiment Analysis
   Classify reviews into Good/ Must-Buy, Neutral/ Mixed-Feedback, and Bad/ Must-Avoid categories. (currently working)

2. Bot Review Detection
   Identify and quantify the percentage of bot-generated reviews (upcoming feature).

3. Contextual and Actionable Insights
   Extract key aspects of reviews and provide detailed insights (upcoming feature).

4. Interactive Dashboard
   A user-friendly Flask-based web interface to input and analyze reviews.

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🛠️ Technologies Used

• Programming Language: Python
• Web Framework: Flask
• NLP: (yet to be finalized)
• Deep Learning: (yet to be finalized)
• Deployment: (yet to be finalized)

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📂 Project Structure

sentify-reviews/
├── app/                   # Flask application
│   ├── templates/         # HTML templates
│   │   ├── base.html
│   │   ├── index.html
│   ├── static/            # CSS, JS, and assets
│   │   ├── css/
│   │   │   └── styles.css            
│   ├── app.py             # Main Flask app
│   ├── sentiment_model/   # Folder for trained models
│   └── utils.py           # Helper functions
├── data/                  # Dataset storage
├── models/                # Training scripts and saved models
├── requirements.txt       # Python dependencies
├── LICENSE                # Project license
└── README.md              # Project overview

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🚀 Usage Workflow

(will be out soon...)

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

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🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Add feature description"

4. Push the branch:

   git push origin feature-name

5. Create a Pull Request.

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🛣️ Roadmap

1. Stage 1: Build and deploy basic sentiment analysis. ⬅️
2. Stage 2: Implement bot review detection.
3. Stage 3: Develop contextual and actionable insights with an interactive dashboard.

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🏷️ Citations & Acknowledgments

(will be out soon...)

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