Update README.md

README.md

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+# YouTube Sentiment Analysis  
+
+## Overview  
+YouTube Sentiment Analysis is a web application that allows users to input a YouTube video link and retrieve comments along with their sentiment analysis. The application employs a machine learning model to determine whether the comments are positive or negative, providing insights into the general opinion of the viewers.  
+
+## Features  
+- **Input Video Link**: Users can enter any valid YouTube video link.  
+- **Sentiment Analysis**: The application analyzes comments' sentiment using AI and provides a detailed summary.  
+- **Styled Comments Table**: Comments are displayed in a table, color-coded based on their sentiment.  
+- **User-Friendly Interface**: Built with Streamlit, providing an intuitive web interface.  
+
+## Technologies Used  
+- **Python**: The primary programming language for the application.  
+- **Streamlit**: For creating interactive web applications.  
+- **Pandas**: For data manipulation and analysis.  
+- **Machine Learning Model**: For predicting the sentiment of the comments.  
+- **YouTube API**: To fetch comments from the specified YouTube videos.  
+
+## Deploying
+- Youtube Sentiment Analysis deployed website: https://alaindelong-youtube-sentiment-analysis.hf.space/
+- Published Model: https://huggingface.co/spaces/AlainDeLong/youtube-sentiment-analysis/tree/main
+- Due to the large size of the model, it cannot be included here; it will be available at the huggingface link mentioned above.
+
+## Installation  
+To set up the project locally, follow these steps:  
+
+1. **Clone the repository**:  
+   ```bash  
+   git clone https://github.com/AlainDeLong2k/demo-youtube-sentiment-analysis.git
+   cd demo-youtube-sentiment-analysis
+
+2. **Create a virtual environment (optional but recommended)**:
+   ```bash
+   python -m venv venv  
+   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
+
+3. **Install the required packages**:
+   ```bash
+   pip install -r requirements.txt
+   
+4. **Run the application**:
+   ```bash
+   streamlit run app.py
+
+## Usage
+1. Open a web browser and navigate to http://localhost:8501 (this is the default Streamlit port).
+2. Enter a valid YouTube video link in the input field. Examples of valid links include:
+   - https://www.youtube.com/watch?v=b5k8bkWYyPQ
+   - https://youtu.be/b5k8bkWYyPQ?si=gABWBqKdjo_um6nk
+3. Click on the `Analyze` button to retrieve and analyze comments for sentiment.
+4. View the summary and comments in the application.
+
+## Contributing
+Contributions are welcome! If you would like to contribute to this project, please fork the repository and submit a pull request with your changes.
+
+## License
+This project is licensed under the MIT License. See the LICENSE file for details.
+
+---
+For any further questions or issues, feel free to open an issue in the repository.
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference