NSF Award
1002499
This Small Business Innovation Research (SBIR) Phase I project will investigate a news/blog analysis system to support the commercialization of a product for market research and trends analysis. By performing natural language / statistical analysis on roughly 1,000 U.S. and international news sources retrieved on a daily basis, the tool can monitor spatial and temporal trends in the presence, reputation, and linkage among news entities such people, places, and companies/organizations. This project will focus on computational research issues associated with improving the performance and versatility of the proposed algorithms for sentiment detection (positive and negative associations) and social network analysis. The effort will also undertake the critical task of transferring the technology from an academic computing environment to a modern cloud computing infrastructure yielding increased reliability and the potential to scale the news analysis to vastly larger-scale text corpuses. <br/><br/>If successful, the news analysis databases created under this proposal will be widely used in a broad range of trends analysis research and applications. It will help business, government and academic researchers to make wiser social and economic decisions, by empowering them to conduct their own primary studies on historical trends and social forces. The market opportunity addressed represents significant commercial potential across a wide range of vertical segments.
