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YouTube Comments Analyzer

YouTube Comments Analyzer

YouTube Comments Analyzer is a powerful web application that allows you to delve into the sentiments expressed by viewers in the comments section of YouTube videos. By leveraging the cutting-edge technologies of Next.js and React, this intuitive tool enables you to gain valuable insights and analyze the emotional reactions of your audience.

Features

🔍 Comment Retrieval: Easily fetch comments from any YouTube video using the YouTube Data API. Explore the sentiments expressed by your viewers without hassle.

📈 Sentiment Analysis: Leverage the Sentiment library to perform advanced sentiment analysis on the retrieved comments. Gain a comprehensive understanding of the emotional tone of the comments.

🌈 Visual Representation: The sentiment analysis results are presented in a visually appealing and intuitive format. The positive, neutral, and negative sentiments are graphically depicted, allowing for quick interpretation and analysis.

💡 User-Friendly Interface: The clean and intuitive user interface ensures a seamless experience. Simply enter the YouTube video link, click the "Go" button, and let the YouTube Comments Analyzer do the rest.

Technologies Used

The YouTube Comments Analyzer utilizes the following technologies:

  • Next.js: A powerful React framework for building efficient and scalable applications.
  • React: A popular JavaScript library for building interactive user interfaces.
  • Sentiment: A robust library for performing sentiment analysis on textual data.
  • YouTube Data API: An API provided by YouTube that enables seamless integration with their data resources.

Getting Started

To run the YouTube Comments Analyzer locally and start exploring the sentiments expressed in YouTube comments, follow these simple steps:

  1. Clone the repository: Begin by cloning this repository to your local machine using the following command: git clone https://github.com/your-username/your-repo.git.
  2. Navigate to the project directory: Move into the cloned repository by executing the command cd your-repo.
  3. Install dependencies: Install the project dependencies by running npm install in your terminal.
  4. Set up API key: Replace the placeholder API key in the fetchComments function with your own YouTube Data API key.
  5. Start the development server: Run npm run dev in your terminal to start the development server.
  6. Explore and analyze: Open your favorite browser and visit http://localhost:3000. Enter a YouTube video link, click "Go," and witness the sentiments come to life!

Usage

Using the YouTube Comments Analyzer is as simple as 1-2-3:

  1. Enter YouTube Video Link: Copy and paste the link of the YouTube video you wish to analyze into the provided input field.
  2. Click "Go": Hit the "Go" button to initiate the retrieval of comments and sentiment analysis.
  3. Visualize the Sentiments: View the sentiment analysis results as captivating visual representations. The positive, neutral, and negative sentiments are depicted using vibrant colors, making it easy to grasp the overall emotional tone of the comments.

License

This project is licensed under the MIT License.

Contributing

Contributions are more than welcome! If you have any suggestions, bug fixes, or enhancements, please feel free to create an issue or submit a pull request. Let's collaborate and make this project even better together!

Acknowledgments

We would like to express our gratitude to the following:

  • The Next.js, React, and Sentiment development teams for their outstanding tools and libraries.
  • The YouTube Data API for providing seamless access to YouTube resources.
  • The open-source community for their continuous support and contributions.

Support

If you encounter any issues, have questions, or would like to provide feedback, please don't hesitate to open an issue on the GitHub repository. Our team will be more than happy to assist you.


Unlock the power of sentiment analysis in YouTube comments with the YouTube Comments Analyzer. Start gaining valuable insights today!

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