Sentiment Analysis Web App

Abstract

This research explores how our approach to seeking information has evolved, particularly in understanding others' perspectives through platforms like online reviews and personal blogs. With the widespread use of technology, there's a growing interest in systems that can handle opinions. The paper focuses on techniques for creating opinion- centric information systems, particularly dealing with challenges in sentiment-aware applications. It categorizes information into facts and opinions, concentrating on expressions of positive or negative sentiments. Using typed dependency parsing, the study investigates the functional connections among words in sentiment analysis, allowing for a thorough examination of grammar and semantics in textual data. emphasizing the role of machine learning in ASP.NET Core for effective feedback and opinion handling.