@inproceedings{3fc9474b5ad746e6b8ffcced98d20589,
title = "Social network intelligence analysis to combat street gang violence",
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 = "Complex networks, Criminology, Social networks",
author = "Damon Paulo and Bradley Fischl and Tanya Markow and Michael Martin and Paulo Shakarian",
year = "2013",
doi = "10.1145/2492517.2500238",
language = "English (US)",
isbn = "9781450322409",
series = "Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013",
publisher = "Association for Computing Machinery",
pages = "1042--1049",
booktitle = "Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013",
note = "2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013 ; Conference date: 25-08-2013 Through 28-08-2013",
}