Sentiment Tech: Exploring the Tools Shaping Emotional Analysis

This chapter illustrates an in-depth study about the contemporary Sentiment Analysis tools and techniques and different approaches, elaborates how researchers, administrator, educators, and other stakeholders may use this capability to extract significant insights from large datasets. It identifies the key methodologies, models, and algorithms applied in the analysis of sentiments expressed. It is laden with technology-driven insights. It explores the intricacies of the world taking sentiment analysis as tools to reveal the hidden emotions in textual/audio/video/social media data. This book chapters explore a detailed analysis of cutting-edge technologies used to find out patterns of the emotional analysis. From Natural Language Processing algorithms to Machine Learning Models, the chapter depicts the diverse tools available for capturing and studying sentiments, whether it is positive, negative, or neutral. With a focus on real-world applications, the chapter discusses the functionalities of the tools used for social media monitoring, customer feedback analysis and beyond. Further, it highlights the ethical considerations and its challenges associated with emotional analysis. “Sentiment Tech” serves as a guide for practitioner, researchers and technologists. The chapter provides a detailed analysis of the tools and technologies shaping Sentiment Analysis in education, offerings to educators, researchers, and technologists for a comprehensive understanding of the evolving landscape and beyond.