Paper Key : IRJ************649
Author: Jayant Neema,Leena Ghatiya,Manas Dhaketa,Mandvee Vatsa
Date Published: 10 May 2024
Abstract
Analyse user-generated content, such as comments or posts, to determine the sentiment of the content. This can help social networks identify negative or harmful content and take action to remove it. Sentiment analysis, a vital branch of natural language processing, involves gauging emotions expressed in text. By determining whether text conveys positive, negative, or neutral sentiment, this technique provides invaluable insights for businesses, researchers, and organizations. It aids in analyzing customer feedback, tracking social media sentiments, conducting market research, and even understanding political dynamics. There are two primary approaches: lexicon-based, which relies on predefined sentiment dictionaries, and machine learning-based, where models are trained to recognize sentiment patterns. Sentiment analysis has become a critical tool for decision-making, brand management, and understanding public opinion in the era of extensive online communication.
DOI LINK : 10.56726/IRJMETS55202 https://www.doi.org/10.56726/IRJMETS55202