Social media reviews and comments on platforms like YouTube have a significant impact on both consumers and manufacturers. Consumers rely on these user-generated opinions to make informed purchasing decisions, while manufacturers use them as feedback for product improvement and market research.
This console application is designed to extract comments from YouTube videos based on a hashtag or a video link, perform sentiment analysis on the comments, and generate a knowledge graph to visualize the sentiment distributions namely positive, negative, neutral and questions ##TECH STACK Natural Language Processing (NLP) Web API Data Visualization Text Processing Graph Theory Web Parsing File Handling Command-Line Interface Data Manipulation File Management Sentiment Analysis API Key Authentication
##WORK FLOW Run the code in a Python environment. Choose an option: Option 1: Search for videos based on a hashtag. Enter a hashtag when prompted. The code will search for videos related to the hashtag using the YouTube Data API. Comments from the videos will be extracted and saved into separate text files based on their sentiment. A knowledge graph will be generated to visualize the sentiment distribution. OPTION 2 - Extract comments from a video link Enter a video link The code will extract comments from the specified YouTube video using the YouTube Data API. The comments will be saved into separate text files based on their sentiment. A knowledge graph will be generated to visualize the sentiment distribution. The knowledge graph is saved as an image file�