Forecasting Dynamic Group Behavior in Social Media

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$100,000.00
Award Year:
2013
Program:
STTR
Phase:
Phase I
Contract:
D13PC00064
Award Id:
n/a
Agency Tracking Number:
D12B-002-0015
Solicitation Year:
2012
Solicitation Topic Code:
ST12B-002
Solicitation Number:
2012.B
Small Business Information
3527 Beverly Glen Blvd., Sherman Oaks, CA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
124668711
Principal Investigator:
Georgiy Levchuk
Simultion&Optimization Engineer
(818) 788-4230
afreedy@percsolutions.com
Business Contact:
Gershon Weltman
Vice President
(818) 788-1025
gweltman@percsolutions.com
Research Institution:
University of Maryland
William Rand
3457 Van Munching
College Park, MD, 20742-
(301) 405-7229
Nonprofit college or university
Abstract
This proposal is to develop a new system for Recognition of Communities and Heterogeneous Analysis of Group Interactions and Dynamics (RC-HAGID) for Social Media Forecasting. Social media enables individuals and groups to quickly coordinate, recruit and direct people to take action in support of a particular objective. This includes terrorist groups and criminal organizations. Accordingly, for full national security it is essential that our intelligence analysts be able to identify and understand the formation and dissolution of groups, interactions between and within groups, and changes in"state"of groups (i.e. from recruitment to carrying out some collaborative action). However, existing techniques for supporting this type of work are limited. In our new and innovative approach, we combine a number of sophisticated techniques that have been developed to address each of the above limitations, and combine them into one integrated system. The resulting tool will be able to monitor social media, identify distinct groups, apply a set of complimentary analyses in order to characterize group"state"and inter- and intra-group interactions based on individual level characteristics in recognition of their heterogeneous nature, forecast changes in group state, and identify the key factors involved with those changes in state.

* information listed above is at the time of submission.

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