Sentiment Analysis - Methods and Applications: Studying methods and applications of sentiment analysis for analyzing and understanding emotions, opinions, and attitudes expressed in text

Abstract

Sentiment analysis, also known as opinion mining, is a computational technique used to determine the emotional tone behind a piece of text. It plays a crucial role in understanding public opinion, customer feedback, and social media trends. This paper provides an overview of sentiment analysis methods and their applications, discussing various techniques, challenges, and future directions in the field. We explore the use of machine learning algorithms, natural language processing (NLP) techniques, and deep learning models for sentiment analysis. Additionally, we discuss the applications of sentiment analysis in business, social media, healthcare, and other domains, highlighting its impact on decision-making processes and user engagement. Through this paper, we aim to provide researchers and practitioners with insights into the methods and applications of sentiment analysis, fostering further advancements in this rapidly evolving field.