@inproceedings{3e7f6a336af94be98bcc0c06851f07be,

title = "STONE: Shaping terrorist organizational network efficiency",

abstract = "This paper focuses primarily on the Person Successor Problem (PSP): when a terrorist is removed from a terrorist network, who is most likely to take his place? We leverage the solution to PSP to predict a new terrorist network after removal of a set of terrorists and to answer the question: which set of κ (κ > 0) terrorists should be removed in order to minimize the lethality of the terrorist network? We propose a theoretical model to study these questions taking into account the fact that terrorists may have different individual capabilities. We develop an algorithm for PSP in which analysts can specify the conditions an individual needs to satisfy in order to replace another person. We test the correctness of our algorithm on a real-world partial network dataset for two terrorist groups: Al-Qaeda and Lashkare-Taiba where we have ground truth about who replaced who, as well as a synthetic dataset where experts estimate who replaced who. Building on the solution to PSP, we develop an algorithm to identify which set of κ people to remove from a terrorist network to minimize the organization's efficiency (formalized as an objective function in some different ways).",

author = "Francesca Spezzano and Subrahmanian, {V. S.} and Aaron Mannes",

year = "2013",

doi = "10.1145/2492517.2492626",

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 = "348--355",

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",

}