Text as Data: Computational Methods of Understanding Written Expression Using SAS

Accurate, efficient, and automated text analysis is proving itself increasingly practical in a variety of fields, including financial management, law enforcement, and customer care. In Text as Data: Computational Methods of Understanding Written Expression Using SAS, expert data scientists Barry DeVille and Gurpreet Singh Bawa deliver a thorough introduction to the framework, dynamics, and underlying principles of text analytics.

They describe the relationship between qualitative-linguistic and quantitative, data-driven aspects of data analysis. The authors also explore the concepts of expression parsing and detection before moving on to an examination of the core principles and practices of text parsing, theme, and topic detection. Advanced topics, like contextual effects in numeric and textual data manipulation, fine-tuning text meaning, and disambiguation, are also covered.

This work offers an overview of text analytics and the central role played by SAS software in combining linguistic and quantitative forms of analysis in this rapidly evolving field. Readers will discover an insightful examination of the evolution of text mining and cloud-based solutions, as well as the development of SAS Visual Text Analytics.

Text as Data provides a compelling argument for the proposition that SAS incorporates superior solutions compared to standard approaches and why text should be treated as qualitative data within a quantitative analytics framework to produce detailed, accurate, and explanatory results. It also explains the role of linguistics, machine learning, and multiple data sources in a typical text analytics workflow.

Text as Data: Computational Methods of Understanding Written Expression Using SAS is ideal for SAS users and data scientists in any industry or academic application. It’s also an indispensable resource for anyone interested in text analytics generally.

Combine the best of qualitative and quantitative techniques within the SAS system for superior results

Text analytics has become an indispensable part of fields as diverse as pharmaceutical research and development and social media marketing. Organizations around the world are implementing comprehensive, text-inclusive analytics strategies.

In Text as Data: Computational Methods of Understanding Written Expression Using SAS, you’ll discover how and why the SAS platform delivers exceptional text analytics results by combining linguistic and quantitative algorithms and treating text as qualitative data from within a quantitative analytics framework.

The accomplished authors offer a thorough introduction to the principles and dynamics of text analytics, along with a comprehensive overview of an effective framework for common use cases. Readers will learn about the interplay between qualitative-linguistic and quantitative data analysis and gain a deep understanding of techniques like expression parsing and detection, text parsing, theme and topic detection, and more. They’ll also discover why SAS is the ideal platform for deploying a text analytics solution.

Ideal for SAS users and data scientists in any industry, Text as Data provides readers with a rich and insightful exploration of text analytics with SAS, creating a foundation for practical and effective applications.