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YouTube Sentiment Analysis Web App

Overview

An interactive web app that leverages NLP to analyze YouTube channel descriptions and video titles, providing insightful sentiment analysis using TextBlob. Built with React, this app turns raw data into visually appealing and understandable information.

Features

• YouTube Channel Analysis: Fetch and analyze channel data including descriptions and video titles.
• Sentiment Analysis: Uses TextBlob to compute sentiment scores and provide insights.
• Interactive UI: Presents results with engaging visuals and friendly descriptions.
• Responsive Design: Ensures a seamless experience across devices.

Tech Stack

• Frontend: React
• Backend: Flask
• Sentiment Analysis: TextBlob
• Data Handling: Google Developer Console APIs
• Styling: CSS

Getting Started

Prerequisites

• Node.js
• npm (or yarn)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/repo-name.git

2. Navigate to the project directory:

   cd repo-name

3. Install dependencies:

   npm install

4. Start the development server:

   npm start

Usage

1. Enter a YouTube channel URL in the input field.
2. Click “Analyze” to fetch and analyze the channel data.
3. View sentiment analysis results presented with visual enhancements.

Contributing

1. Fork the repository.
2. Create a new branch for your feature:

   git checkout -b feature/YourFeatureName

3. Commit your changes:

   git commit -m 'Add new feature'

4. Push to the branch:

   git push origin feature/YourFeatureName

5. Create a pull request.

Contact

For questions or feedback, please reach out to connectsaimm@gmail.com.

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