Monthly Archives: June 2013

As CEO and chief scientist at Strategic Analysis Enterprises, Inc., Steve Shellman is responsible for developing qualitative and quantitative analytic systems that allow clients to understand, predict, and influence events, behavior, and popular beliefs. Steve Shellman and Strategic Analysis Enterprises, Inc., use academic methodology to develop tools and strategies for solving real world problems. 

With the rise of social media and user-created content, sentiment analysis is becoming increasingly important for gauging the actions, reactions, and beliefs of consumers, writers, and others who create internet content about any number of topics. It is virtually impossible to manually read and interpret the vast amount of information stored online. Thus, data analysis researchers and companies have developed sophisticated tools that automatically mine and analyze web content.

These sentiment analysis tools serve a variety of purposes for political, corporate, and media interests. Businesses use sentiment analysis to gain information about customers and their opinions, thereby more effectively marketing their products and finding new audiences. Governments and politicians employ analysis tools in gauging, and even generating, support for a political candidate or platform. Media and news outlets, most of which operate at least partially online, work to understand public interest through analysis of reader-generated comments.

In 2008, Stephen M. Shellman founded Strategic Analysis Enterprises, Inc., to help support government agencies making national-scale decisions. The company has since worked on projects for the U.S. Department of Defense, the Joint Staff, and U.S. Strategic Command. It also did major subcontract work on the Integrated Crisis Early Warning System (ICEWS), a project funded by the Defense Advanced Research Projects Agency (DARPA).

DARPA funded ICEWS to create a platform that could reliably forecast upheaval and violence. It makes use of three major planks. First, it uses natural language processing to take unstructured news reports and turn them into quantitative indices. Second, it combines that data with other data to generate continuous forecasts of rebellions, international crises, insurgencies, and ethnic or religious violence. Third, it combs news feeds and blogs to measure public sentiment about events and organizations in a region.

ICEWS was created with a focus on the operations area of the U.S. Pacific Command. ONR extended the DARPA ICEWS project to the world. The Worldwide ICEWS or WICEWS project now includes global coverage of crises worldwide.