Computational Intelligence for Sentiment Analysis in Natural Language Processing Applications provides a solution to this problem through detailed technical coverage of AI-based Sentiment Analysis methods for various applications. The book's authors provide readers with an in-depth look at the challenges and associated solutions, including case studies and real-world scenarios from across the globe. Development of scientific and enterprise applications are covered that will aid computer scientists in building practicalreal-world AI-based Sentiment Analysis systems. With the vast increase in Big Data, computational intelligence approaches have become a necessity for Natural Language Processing (NLP) and Sentiment Analysis in a wide range of decision-making application areas. The opinions registered by the users on a specific subject is collectively analyzed to provide a final comment on the subject. Analyzing these data is a tedious task that can be solved by Machine Learning (ML) techniques. Hence, the combination of sentiments and ML techniques is extremely important to derive any information from the huge social media data. In this book, different types of ML and deep learning methods are explored in the context of different dimensions of sentiment analysis.