Practical Text Analytics

Maximizing the Value of Text Data

By: Chelsey Hill, Thomas Nolan, Murugan Anandarajan

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Paperback | 21 December 2018

At a Glance

Paperback
316 Pages

Dimensions(cm)
23.5 x 15.49 x 1.68

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This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media.

Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.

Industry Reviews

"The book also eases readers' comprehension by presenting a short introduction and illustrating some key takeaways ... . This book is relatively suitable for newcomers in the field of text data analytics, especially for students and researchers who do not excel in statistics but still hope to use big data to lay a sound foundation for their research. Hopefully, the book can elucidate readers to step into the wonderful world of text data analytics." (Jianwei Qian and Rob Law, Information Technology & Tourism, Vol. 21, 2019)

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