The soma terror organization portal (Stop): Social network and analytic tools for the real-time analysis of terror groups

Amy Sliva, V. S. Subrahmanian, Vanina Martinez, Gerardo I. Simari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Stochastic Opponent Modeling Agents (SOMA) have been proposed as a paradigm for reasoning about cultural groups, terror groups, and other socio-economic-political-military organizations worldwide. In this paper, we describe the SOMA Terror Organization Portal (STOP). STOP provides a single point of contact through which analysts may access data about terror groups world wide. In order to analyze this data, SOMA provides three major components: the SOMA Extraction Engine (SEE), the SOMA Adversarial Forecast Engine (SAFE), and the SOMA Analyst NEtwork (SANE) that allows analysts to find other analysts doing similar work, share findings with them, and let consensus findings emerge. This paper describes the STOP framework.

Original languageEnglish (US)
Title of host publicationSocial Computing, Behavioral Modeling, and Prediction, 2008
EditorsJohn J. Salerno, Michael J. Young, Huan Liu
PublisherSpringer
Pages9-18
Number of pages10
ISBN (Print)9780387776712
DOIs
StatePublished - 2008
Externally publishedYes
Event1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008 - Phoenix, United States
Duration: Apr 1 2008Apr 2 2008

Publication series

NameSocial Computing, Behavioral Modeling, and Prediction, 2008

Conference

Conference1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008
Country/TerritoryUnited States
CityPhoenix
Period4/1/084/2/08

ASJC Scopus subject areas

  • Modeling and Simulation

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