This project enables real-time sentiment analysis of YouTube video comments to help users gauge audience reactions. Built with a Python Flask backend and a React frontend, it uses the YouTube Data API to fetch live comments and applies natural language processing (via TextBlob) to classify them as positive, neutral, or negative. Designed with a clean and modern interface, the tool delivers immediate feedback, making it valuable not only for content creators aiming to refine their content strategies but also for marketers analyzing campaign impact, researchers studying opinion trends, and educators or media professionals monitoring public discourse. By offering instant insights into viewer sentiment, the project serves as a powerful decision-making aid across industries that rely on audience engagement and feedback.