KumarUtsav1025/youtube_sentiment_extension

YOUTUBE_SENTIMENT_EXTENSION

Developed with the software and tools below.

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Quick Links

• Overview
• Features
• Repository Structure
• Getting Started
  • Installation
  • Running youtube_sentiment_extension
• Contributing
• License

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Overview

The YouTube Comment Sentiment Analyzer is a Chrome extension designed to help users quickly gauge the sentiment of comments on YouTube videos. By analyzing the first 20 comments on a video, this tool provides an overview of the audience's sentiment, categorizing comments as positive, negative, or neutral.

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Features

• Sentiment Analysis: Automatically analyzes the first 20 comments on a YouTube video.
• Sentiment Categories: Classifies comments into positive, negative, or neutral.
• User-Friendly Interface: Displays results in an easy-to-understand format.
• Quick Access: Accessible directly from the Chrome toolbar while watching a YouTube video.

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Repository Structure

└── youtube_sentiment_extension/
    ├── background.js
    ├── content.js
    ├── images
    │   ├── icon16.png
    │   ├── loading.gif
    │   ├── negative.gif
    │   ├── neutral.gif
    │   ├── positive.gif
    │   ├── sad.gif
    │   ├── truck.gif
    │   └── youtube-animation.gif
    ├── manifest.json
    ├── popup.html
    ├── script.js
    └── styles.css

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Getting Started

Requirements

Ensure you have the following dependencies installed on your system:

• JavaScript: version x.y.z

Installation

1. Clone the youtube_sentiment_extension repository:

git clone https://github.com/KumarUtsav1025/youtube_sentiment_extension

2. Change to the project directory:

cd youtube_sentiment_extension

Running youtube_sentiment_extension

• Open Chrome and navigate to the Extensions page:

  chrome://extensions/

• Enable Developer Mode by clicking the toggle switch in the top right corner.
• Click "Load unpacked" and select the cloned directory.

Usage

• Navigate to a YouTube video.
• Click on the YouTube Comment Sentiment Analyzer icon in the Chrome toolbar.
• The extension will automatically fetch and analyze the first 20 comments.
• View the sentiment analysis results displayed in the extension popup.

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Contributing

Contributions are welcome! Here are several ways you can contribute:

• Submit Pull Requests: Review open PRs, and submit your own PRs.
• Join the Discussions: Share your insights, provide feedback, or ask questions.
• Report Issues: Submit bugs found or log feature requests for Youtube_sentiment_extension.

Contributing Guidelines

1. Fork the Repository: Start by forking the project repository to your GitHub account.
2. Clone Locally: Clone the forked repository to your local machine using a Git client.

   git clone https://github.com/KumarUtsav1025/youtube_sentiment_extension

3. Create a New Branch: Always work on a new branch, giving it a descriptive name.

   git checkout -b new-feature-x

4. Make Your Changes: Develop and test your changes locally.
5. Commit Your Changes: Commit with a clear message describing your updates.

   git commit -m 'Implemented new feature x.'

6. Push to GitHub: Push the changes to your forked repository.

   git push origin new-feature-x

7. Submit a Pull Request: Create a PR against the original project repository. Clearly describe the changes and their motivations.

Once your PR is reviewed and approved, it will be merged into the main branch.

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Other Links

• For more details on the machine learning classification model used in this project, visit the following repository: ML Classification Model Repository

• To see the server deployment for this project, check out this repository: Server Deployment Repository

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License

This project is protected under the MIT License. For more details, refer to the LICENSE file.

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