Automated Sentiment Detection on Social Media Post and Product Reviews Using Flash

The project is a web-based platform for sentiment analysis built with Flask that lets users gather, examine, and evaluate user-generated comments on Reddit and YouTube.Each user can maintain and retrieve their own analysis history thanks to its secure login system.Once signed in, users are able to input a keyword, hashtag, or topic of interest and select their chosen platform.The program uses PRAW for Reddit and the YouTube Data API for YouTube to retrieve pertinent comments.The emotional tone (positive, negative, or neutral) and, if relevant, the subjectivity of each comment is then ascertained through analysis with Natural Language techniques Processing (NLP) tools, particularly TextBlob and VADER.The outcomes are displayed in an interactive dashboard that displays the overall sentiment classification, average polarity score, a complete table of comments with their corresponding sentiment labels, and a pie graphic showing the distribution of sentiment.Because all processed data is safely kept in a MySQL database, users can keep their results for reporting, trend analysis, and future reference.By combining automated data collection, sentiment evaluation, visual representation, and secure data storage, the platform delivers an integrated and practical solution for understanding public opinion across social media platforms.