Machine Learning and Sentiments Analysis

Abstract

A significant amount of user-generated material, notably in the form of customer evaluations, has been produced in recent years as a result of the exponential rise of digital platforms. Utilizing this vast amount of data through cutting-edge methods like machine learning and sentiment analysis has become essential for organizations looking to learn insightful things about their customers' attitudes. This chapter explores how machine learning and sentiment analysis dynamically intersect when used to analyze customer evaluations. The chapter analyses how machine learning algorithms can be efficiently used to uncover complex patterns and feelings hidden in various consumer feedback through a thorough study. By using cutting-edge methodology, it reveals the intrinsic polarity and emotional undertones of these evaluations, offering insightful information about how customers feel. The chapter further illustrates how machine learning-driven sentiment analysis is used in practice across a variety of industries, shedding light on how it influences strategic business choices.