Sentiment Analysis using Machine Learning Algorithms

Abstract

Sentiment analysis has grown in importance in both the scientific and commercial spheres as a result of its enormous potential to completely transform a wide range of sectors. Many companies have responded to this increasing significance by incorporating sentiment analysis and customer perception as essential elements of their overall strategies. But the automated analysis of social network posts, where the rich tapestry of human emotions and expressions is sewn, is one of the most fascinating uses of sentiment analysis. This chapter sets out on a revolutionary adventure to bridge the gap between the sophisticated emotional fabric of social networks and the state-of-the-art sentiment-based approaches and technology that have the potential to completely change this rapidly developing field. The main result of our investigation is a thorough study, a complex tapestry in and of itself, that presents the most engaging and cutting-edge methods for the comparison and classification of communications in the ever-changing world of social media platforms. This survey includes a thorough explanation of cutting-edge methods and technologies that have the potential to revolutionize sentiment research and shed light on the complexities of human emotion in the digital era.