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Socio-computational Methods to Detect and Predict Bot Activity in Novel Information Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-15-P-1187
Agency Tracking Number: N15A-020-0195
Amount: $80,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N15A-T020
Solicitation Number: 2015.1
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-07-06
Award End Date (Contract End Date): 2016-05-06
Small Business Information
15400 Calhoun Drive
Rockville, MD 20855
United States
DUNS: 181423752
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Onur Savas
 (301) 294-4241
Business Contact
 Mark James
Title: Technical Point of Contact
Phone: (301) 294-5221
Research Institution
 University of Arkansas of Little Ro
 Nitin Agarwal
2801 S. University Ave.
Little Rock, AZ 72204
United States

 (501) 683-7155
 Domestic Nonprofit Research Organization

Intelligent Automation, Inc. (IAI) proposes to understand social bots behaviors, extract indicators, develop socio-computational models with predictive capabilities to detect bot activity, and implement them in a mature social media analytics software tool. Our approach will use predictive socio-computational models that exploit context, user, friends, temporal, and network features of social media users. Our models will be matured to further understand emerging sociotechnical behaviors for conflict monitoring and social bots activities from organizational and tactical perspectives. We will exploit adaptive machine learning to efficiently refine our models as bot behaviors and social media landscape change over time. By identifying correlation of bot detection and other social media analytics (e.g., influence detection, community detection), we will enhance bot detection by (i) identifying top propaganda disseminators and polarizers, and (ii) extracting influential coordination structures within social bots. The uncertainty and trustworthiness of analytical results will also be computed, and interactive visualization will further help the analysts to drill down and filter. The models and algorithms will then be implemented and integrated with IAIs social media analytics tool that provides advanced analytics capabilities, search, and visualization in a Data Science as a Service (DSaaS) framework.

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

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