{"id":20147273,"url":"https://github.com/machphy/youtube_sentiment_analysis_api","last_synced_at":"2026-01-28T14:33:28.498Z","repository":{"id":250326533,"uuid":"834141437","full_name":"machphy/youtube_sentiment_analysis_API","owner":"machphy","description":"analyzes sentiment in YouTube video comments using the YouTube Data API and a pre-trained model. It fetches comments, performs sentiment analysis, and visualizes the results on a web interface.  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The application uses the YouTube Data API to fetch comments and then analyzes their sentiment using a pre-trained model. Results are visualized and displayed on a web interface.**\n\nSentiment Analysis is a popular application of Natural Language Processing (NLP). This project focuses on analyzing YouTube comments to understand the sentiments expressed by viewers.\n\n\u003cbr\u003e\n\n## Live Link\n**Hosted on GitHub Pages**\n\n### 🔗 [Live Demo Link](https://github.com/machphy/youtube_sentiment_analysis_API)\n\n\u003cbr\u003e\n\n## Project Specifications\n\n**Below are the libraries and frameworks used to create the project:**\n- **Web Framework:** Flask\n- **Visualization:** Matplotlib\n- **Sentiment Analysis Libraries:** TensorFlow/Keras\n- **API Requests:** `requests`\n\n\u003cbr\u003e\n\n## Project Components\n\n**The project currently includes:**\n1. **Comment Analysis** - Fetches comments from a YouTube video using the YouTube Data API and analyzes their sentiment.\n2. **Visualization** - Displays sentiment distribution and insights using charts.\n\n\u003cbr\u003e\n\n## Screenshots\n\n**Application Interface**\n\n![Screenshot 2024-07-26 185950](doc/Screenshot%202024-07-26%20185950.png)\n\n**Sentiment Analysis Results**\n\n![Screenshot 2024-07-26 190011](doc/Screenshot%202024-07-26%20190011.png)\n\n\u003cbr\u003e\n\n\n\u003cbr\u003e\n\n## Important Information\n\n### **YouTube Data API**\n\nAPI documentation link - [YouTube Data API Documentation](https://developers.google.com/youtube/v3/docs)\n\n\u003cbr\u003e\n\nTo work with the API, you need to **create an API key**.\nTo create an API key, **register** on the Google Cloud Console and a unique key will be generated for you. Use this key to make successful API requests.\n\n**Note:** Ensure your API key is kept secure and adhere to usage limits.\n\n\u003cbr\u003e\n\n### **API Specifications**\nTo fetch comments, the application performs the following API calls:\n1. **Fetch Comments** - Retrieve comments for a YouTube video using the YouTube Data API.\n2. **Analyze Sentiment** - Process the comments and analyze their sentiment.\n\n**API Endpoint for Comments** - `https://www.googleapis.com/youtube/v3/commentThreads?part=snippet\u0026videoId={videoId}\u0026key={apiKey}`\n\n\u003cbr\u003e\n\n## Models Used\nThe project uses pre-trained models for sentiment analysis. Here’s a brief overview of the tools used:\n\n- **TensorFlow/Keras** - Libraries for building and using machine learning models for sentiment analysis.\n\n\u003cbr\u003e\n\n*__Note:__*\n1. The sentiment analysis model classifies comments into sentiment categories (POSITIVE🙂, NEGATIVE☹️, NEUTRAL😐).\n\n\u003cbr\u003e\n\n## Project Development Ideas\n\n**Future enhancements may include:**\n- Analyzing comments in different languages.\n- Integrating with other social media platforms.\n- Enhancing visualizations with interactive charts.\n\n\u003cbr\u003e\n\n## Thank You!\nThank you for exploring the project. **I hope you find it useful**. \n\nIf you did, please consider **giving a star**⭐ to this repository. It would mean a lot!\n\n\u003cbr\u003e\n\n---\n\n© 2024 Rajeev Sharma | [rajeevsharmamachphy@gmail.com](mailto:rajeevsharmamachphy@gmail.com)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmachphy%2Fyoutube_sentiment_analysis_api","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmachphy%2Fyoutube_sentiment_analysis_api","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmachphy%2Fyoutube_sentiment_analysis_api/lists"}