/Restaurant-Review-Analysis-System

Restaurant Review System is a Flask-based web application that allows restaurant owners to analyze and visualize customer reviews. This platform leverages natural language processing (NLP) techniques using the Natural Language Toolkit (NLTK) and TextBlob in Python.

Primary LanguageHTMLMIT LicenseMIT

Restaurant Review System

Restaurant Review System is a Flask-based web application that allows restaurant owners to analyze and visualize customer reviews. This platform leverages natural language processing (NLP) techniques using the Natural Language Toolkit (NLTK) and TextBlob in Python. The system enables users to perform sentiment analysis on individual reviews or upload a text file containing multiple reviews for comprehensive analysis. The user-friendly interface ensures easy navigation and understanding of the sentiment analysis results, which are presented through interactive visualizations.

The user interface is designed with simplicity in mind, utilizing Bootstrap CSS to ensure a clean and responsive design.

Live Demo ---> Render

intro img

Features

  • Sentiment Analysis: Analyzes the sentiment of individual customer reviews or a batch of reviews from a text file, providing scores for positive, negative, neutral, and compound sentiments using NLTK's VADER and TextBlob.
  • Aspect-Based Sentiment Analysis: Identifies and analyzes sentiments towards specific aspects of the restaurant experience, such as service, food, and ambiance.
  • File Upload for Batch Analysis: Allows users to upload a text file containing multiple customer reviews, enabling batch processing and analysis of reviews.
  • Analytics Dashboard: Provides a visual dashboard to display sentiment trends over time, aspect-based sentiment breakdowns, and other analytical insights using interactive charts.
  • Interactive Visualizations: Utilizes Chart.js and Plotly to create engaging and interactive charts and graphs that help restaurant owners better understand customer feedback and sentiment trends.

Directory Structure

Restaurant-Review-System/
│
├── app.py                  # Flask application code
├── templates/              # HTML templates
│   ├── index.html          # Main page template
│   ├── upload.html         # Upload page template
│   └── dashboard.html      # Dashboard page template
├── uploads/                # Directory for uploaded files
├── README.md               # Project overview and instructions
└── requirements.txt        # Python dependencies

How to Use

  1. Clone the Repository:

    git clone https://github.com/Vikranth3140/Restaurant-Review-Analysis-System.git
cd Restaurant-Review-Analysis-System

  2. Install Dependencies:

    pip install -r requirements.txt

  3. Run the Application:

    python app.py

  4. Access the Web Interface:

    • Open your browser and go to http://localhost:5000.
    • Enter a customer review in the provided form and click "Analyze Sentiment" to see the sentiment analysis results.
    • Click on Upload Reviews File to upload a text file containing multiple reviews for batch analysis.
    • Navigate to the Dashboard to view visualizations and analytical insights of the sentiment analysis results.

License

This project is licensed under the MIT License.