Advanced Sentiment Analysis and Topic Extraction Annotation Framework for YouTube Comments

The YouTube Sentiment Analyzer and annotation framework research study aims to provide a robust solution for analyzing YouTube videos through summarization, sentiment analysis, and transcript generation. It incorporates Whisper for speech-to-text transcription of videos lacking transcripts, while videos with available transcripts are processed using the YouTube Transcript API. The tool generates concise summaries and identifies key insights from the video content, analyzing sentiment to determine its overall tone and user engagement. By leveraging Groq’s API for summarization and Streamlit for the user interface, along with Seaborn for data visualization and WordCloud for keyword analysis, this research study delivers a user-friendly experience for quickly understanding video content.