Sentiment Analysis: Concepts, Techniques and Applications

About this Book

Sentiment Analysis: Concepts, Techniques and Applications is a comprehensive academic textbook that introduces readers to the principles, methodologies, and practical applications of sentiment analysis and Natural Language Processing (NLP). Designed for beginner to intermediate learners, the book provides a structured understanding of classical machine learning techniques, deep learning models, transformer architectures, and multilingual sentiment analysis. The book covers the complete sentiment analysis workflow, including data collection, preprocessing, feature extraction, lexicon-based methods, machine learning algorithms, deep learning techniques, and transformer-based language models. Special emphasis is placed on multilingual and low-resource language processing, with dedicated chapters on Tamil and Malayalam sentiment analysis, code-mixed text, transliteration, multilingual transformers, transfer learning, and fine-tuning strategies. In addition to theoretical concepts, the book includes practical examples, workflow diagrams, comparison tables, algorithms, case studies, and real-world applications across domains such as social media analytics, healthcare, e-commerce, finance, and explainable artificial intelligence. Emerging topics including Large Language Models (LLMs), multimodal sentiment analysis, and future research directions are also discussed. This book serves as an ideal resource for undergraduate and postgraduate students, researchers, academicians, and industry professionals seeking a solid foundation in modern sentiment analysis and multilingual Natural Language Processing.

Technical Specifications

About the Authors