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SEmantic Context Aware Network Tools (SECANT)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-13-C-0035
Agency Tracking Number: A12A-009-0091
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A12a-T009
Solicitation Number: 2012.A
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2012-12-31
Award End Date (Contract End Date): 2013-06-16
Small Business Information
1235 South Clark Street Suite 400
Arlington, VA -
United States
DUNS: 036593457
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Tim Hawes
 (703) 414-5032
Business Contact
 Dana Ho
Title: Contracts Manager
Phone: (703) 414-5016
Research Institution
 Cornell University
 Jeffrey Hancock
320 Kennedy Hall
Ithaca, NY 14853-
United States

 (607) 255-4452
 Nonprofit College or University

Social network analysis has become one of the most powerful analytic tools in both private and government sectors and a key source of information on individuals and groups. Recently, social media arose as an important source for social network data in both sectors. Unfortunately, theoretically motivated approaches to social network analysis have not been able to keep pace with the new informational character of social media. Social media offers a previously unheard of volume and variety of data making possible richer analyses, but also introducing greater levels of complexity and noise. We propose a system called SEmantic Context Aware Network Tools (SECANT). SECANT is motivated by the observation that traditional research methodologies in the fields of structural network analysis, sociologically and psychologically theory and content mining each contain gaps the other fields can fill. The goal of SECANT is to enable hybrid methodologies from these fields that will produce analytic tools which yield more meaningful and relevant results. SECANT blends the scalability of traditional SNA with sociology"s awareness of social context, and content mining"s awareness of semantic context of its base fields to accomplish this goal.

* Information listed above is at the time of submission. *

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