@inproceedings{73b24aa647254fe9b3893bf6da08dc3e,
title = "Application of a profile similarity methodology for identifying terrorist groups that use or pursue CBRN weapons",
abstract = "No single profile fits all CBRN-active groups, and therefore it is important to identify multiple profiles. In the analysis of terrorist organizations, linear and generalized regression modeling provide a set of tools to apply to data that is in the form of cases (named groups) by variables (traits and behaviors of the groups). We turn the conventional regression modeling {"}inside out{"} to reveal a network of relations among the cases on the basis of their attribute and behavioral similarity. We show that a network of profile similarity among the cases is built in to standard regression modeling, and that the exploitation of this aspect leads to new insights helpful in the identification of multiple profiles for actors. Our application builds on a study of 108 Islamic jihadist organizations that predicts use or pursuit of CBRN weapons.",
keywords = "CBRN use or pursuit, Networks, profile similarity, terrorism",
author = "Breiger, {Ronald L.} and Ackerman, {Gary A.} and Victor Asal and David Melamed and Milward, {H. Brinton} and Rethemeyer, {R. Karl} and Eric Schoon",
year = "2011",
doi = "10.1007/978-3-642-19656-0_5",
language = "English (US)",
isbn = "9783642196553",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "26--33",
booktitle = "Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings",
note = "4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011 ; Conference date: 29-03-2011 Through 31-03-2011",
}