Sentiment analysis categorizes the emotional tone of text, using natural language processing and machine learning. It helps businesses gain insights from customer feedback, social media, and more, to understand public opinion, make data-driven decisions, and manage brand reputation.
A comprehensive local product research system that scrapes product data, analyzes reviews using NLP, tracks price trends, and provides AI-powered insights and recommendations. Uses n8n
YouTube Comment Sentiment Analyzer is a Python-based web application that analyzes the sentiment of comments from any YouTube video. It uses the YouTube Data API to fetch comments, processes them using the VaderSentiment library, and displays the result as a bar graph showing positive, negative, and neutral sentiments.
Add a description, image, and links to the sentiments-analysis topic page so that developers can more easily learn about it.
To associate your repository with the sentiments-analysis topic, visit your repo's landing page and select "manage topics."