We are pleased to share the publication of Text Analytics in Marketing: A Practical Guide for Students and Researchers, a new book by Daniel Dan and Thomas Reutterer.

The book offers an accessible introduction to text analytics for marketing and shows how textual data can be used to generate useful insights from reviews, social media content, surveys, and other forms of user generated content. It covers key methods for analyzing, reducing, classifying, and visualizing text, with a strong focus on applications in marketing and the use of R.

With many examples, code snippets, and exercises, the book is aimed at students, researchers, and practitioners who want to build practical skills in text based marketing analysis. Topics include data collection, preprocessing, clustering, text classification, topic modeling, sentiment analysis, named entity recognition, and transformer based approaches.

The book is available via Springer, and a companion site offers additional supporting material.

View on Springer

Visit Companion Site