The U.S. Department of Homeland Security is funding a research project designed to teach computers to scan text and then sort opinion from fact.

The project involves Cornell University Professor of Computer Science Claire Cardie and associate professors of computer science Janyce Wiebe of the University of Pittsburgh and Ellen Riloff of the University of Utah.

The consortium is one of four University Affiliate Centers to conduct research on advanced methods for information analysis and to develop computational technologies that contribute to national security.

Lots of work has been done on extracting factual information -- the who, what, where, when, explained Cardie. We're interested in seeing how we would extract information about opinions.

The scientists will use machine-learning algorithms to give computers examples of text expressing both fact and opinion and then teach them to tell the difference.