Case Studies
From the chapters in this book you have learned so far about text analytics concepts and read about applications of those concepts using the SAS Text Analytics suite. Going with the famous quote from Benjamin Franklin, “Tell me and I forget. Teach me and I remember. Involve me and I learn,” as much as understanding concepts and theory via reading of chapters are important, perhaps real case studies with detailed applications of tools are more important from a learning perspective. One of the key objectives of this book is to provide you, the reader, an opportunity to try hands-on applications of most of the concepts and tools discussed in this book.
This book contains nine case studies. Each case study has step-by-step instructions on how to perform text analytics using different SAS tools. We have provided you with access to data for seven case studies. Case Study 8 is a demonstration on the new web-based application that combines the power of SAS® Text Miner and SAS® Content Categorization in a single interface called SAS® Contextual Analysis. The data for this case study is not currently available.
The table below lists the SAS Text Analytics tools used in each of the case studies.
| Case Study | Title | SAS Text Analytics Tools |
| 1 | Text mining SUGI/SAS Global Forum paper abstracts to Reveal Trends | SAS® Text Miner |
| 2 | Automatic Detection of Section Membership for SAS Conference Paper Abstract Submissions | SAS® Text Miner, |
| SAS® Enterprise Content Categorization | ||
| 3 | Features-based Sentiment Analysis of Customer Reviews | SAS® Text Miner, |
| SAS® Sentiment Analysis Studio, | ||
| SAS® Enterprise Content Categorization | ||
| 4 | Exploring Injury Data for Root Causal and Association Analysis | SAS® Text Miner, |
| SAS® Enterprise Content Categorization | ||
| 5 | Enhancing Predictive Models Using Textual Data | SAS® Text Miner |
| 6 | Opinion Mining of Professional Drivers’ Feedback | SAS® Text Miner, |
| SAS® Sentiment Analysis Studio | ||
| 7 | Information Organization and Access of Enron Emails to Help Investigation | SAS® Information Retrieval Studio, |
| SAS® Text Miner, | ||
| SAS® Enterprise Content Categorization | ||
| 8 | Unleashing the Power of Unified Text Analytics to Categorize Call Center Data | SAS® Contextual Analysis, |
| 9 | Evaluating Health Provider Service Performance Using Textual Responses | SAS® Text Miner, |
| SAS® Sentiment Analysis Studio |