GENNET: Advanced System for Synthesis of High Fidelity Social Networks to support SHIELD

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$99,944.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
W31P4Q-12-C-0040
Agency Tracking Number:
11SB2-0090
Solicitation Year:
2011
Solicitation Topic Code:
SB112-004
Solicitation Number:
2011.2
Small Business Information
Carley Technologies, Inc.
1924 Glen Mitchell Road, Sewickley, PA, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
Y
Duns:
801266102
Principal Investigator:
Eric Malloy
Senior System Engineer
(412) 953-8818
eric.malloy@carleytech.com
Business Contact:
Larry Carley
Chief Financial Officer
(412) 953-8818
rick.carley@carleytech.com
Research Institution:
Stub




Abstract
Our objective is to provide a semi-automated system to generate and verify scalable, high fidelity, multi-dimensional, social networks with realistic distributional, temporal and spatial characteristics. This will enable the user to generate networks varying in size, node attributes, geo-temporal characteristics, consistency with other networks, and reflection of known subpopulations, in formats used by standard network analytic packages. Generative algorithms will be informed by empirical data and theoretical findings about network generation. We build synthetic networks using a multi-algorithm approach employing subpopulation identification, empirical seeding, constraint satisfaction, and multi-network alignment. Synthesized networks are compared against real networks varying in size, media usage, and activities conducted by network members. Veridicality is assessed on multiple dimensions; network density, distribution of centrality measures, temporal characteristics, spatial characteristics, and evolutionary properties. Deltas between temporal slices will be validated for key actors and topologies at both the subpopulation level and overall network level. Each aspect will be compared to corresponding measurements in known networks at the node, group, motif, and topology levels. A secondary feature of the proposed system will be the ability to layer onto the synthetic network hidden covert networks or purposive networks designed to accomplish some task.

* information listed above is at the time of submission.

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