Learn to assess textual data and extract sentiments using various text analysis R packages


  • In-depth coverage on core principles, challenges, and application of Emotion Analysis.
  • Includes real-world examples to simplify practical uses of R, Shiny, and various popular NLP techniques.
  • Covers different strategies used in Sentiment and Emotion Analysis.


This book covers how to conduct Emotion Analysis based on Lexicons. Through a detailed code walkthrough, the book will explain how to develop systems for Sentiment and Emotion Analysis from popular sources of data, including WhatsApp, Twitter, etc.

The book starts with a discussion on R programming and Shiny programming as these will lay the foundation for the system to be developed for Emotion Analysis. Then, the book discusses essentials of Sentiment Analysis and Emotion Analysis. The book then proceeds to build Shiny applications for Emotion Analysis. The book rounds off with creating a tool for Emotion Analysis from the data obtained from Twitter and WhatsApp.

Emotion Analysis can be also performed using Machine Learning. However, this requires labeled data. This is a logical next step after reading this book. 


  • Learn the essentials of Sentiment Analysis.
  • Learn the essentials of Emotion Analysis.
  • Conducting Emotion Analysis using Lexicons.
  • Learn to develop Shiny applications.
  • Understanding the essentials of R programming for developing systems for Emotion Analysis.


This book aspires to teach NLP users, ML engineers, and AI engineers who want to develop a strong understanding of Emotion and Sentiment Analysis. No prior knowledge of R programming is needed. All you need is just an open mind to learn and explore this concept.