Analysis of Unstructured Data: Applications of Text Analytics and Sentiment Mining
Goutam Chakraborty · 2014
The proliferation of textual data in business is overwhelming. Unstructured textual data is being constantly generated via call center logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, and so on. While the amount of textual data is increasing rapidly, businesses ’ ability to summarize, understand, and make sense of such data for making better business decisions remain challenging. This paper takes a quick look at how to organize and analyze textual data for extracting insightful customer intelligence from a large collection of documents and for using such information to improve business operations and performance. Multiple business applications of case studies using real data that demonstrate applications of text analytics and sentiment mining using SAS ® Text Miner and SAS ® Sentiment Analysis Studio are presented. While SAS ® products are used as tools for demonstration only, the topics and theories covered are generic (not tool specific).