Paper Info
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 k (k 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 Lashkar-e-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 k people to remove from a terrorist network to minimize the organization's efficiency (formalized as an objective function in some different ways).
Year
DOI
Venue
2013
10.1145/2492517.2492626
ASONAM
Keywords
Field
DocType
terrorist organizational network efficiency,different way,terrorist network,person successor problem,new terrorist network,terrorist group,individual need,synthetic dataset,real-world partial network dataset,different individual capability,k people,terrorism,topic models,evaluation,prediction
Data mining,Leverage (finance),Successor cardinal,Computer science,Computer security,Terrorism,Correctness,Operations research,Artificial intelligence,Topic model,Machine learning
Conference
Citations 
PageRank 
References 
2
0.39
7
Authors
3
Name
Order
Citations
PageRank
Francesca Spezzano18019.08
V. S. Subrahmanian268641053.38
Aaron Mannes3232.98