DocumentCode :
1825369
Title :
Social network intelligence analysis to combat street gang violence
Author :
Paulo, Damon ; Fischl, Bradley ; Markow, Tanya ; Martin, Miquel ; Shakarian, Paulo
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., U.S. Mil. Acad., West Point, NY, USA
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
1042
Lastpage :
1049
Abstract :
In this paper we introduce the Organization, Relationship, and Contact Analyzer (ORCA) that is designed to aide intelligence analysis for law enforcement operations against violent street gangs. ORCA is designed to address several police analytical needs concerning street gangs using new techniques in social network analysis. Specifically, it can determine “degree of membership” for individuals who do not admit to membership in a street gang, quickly identify sets of influential individuals (under the tipping model), and identify criminal ecosystems by decomposing gangs into sub-groups. We describe this software and the design decisions considered in building an intelligence analysis tool created specifically for countering violent street gangs as well as provide results based on conducting analysis on real-world police data provided by a major American metropolitan police department who is partnering with us and currently deploying this system for real-world use.
Keywords :
police data processing; social networking (online); American metropolitan police department; ORCA; criminal ecosystems; design decisions; intelligence analysis tool; law enforcement operations; membership degree; organization relationship and contact analyzer; police analytical needs; real-world police data; social network analysis; social network intelligence analysis; street gang violence; tipping model; Law enforcement; complex networks; criminology; social networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON
Type :
conf
Filename :
6785829
Link To Document :
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