Ranking terrorists in networks: A sensitivity analysis of Al Qaeda's 9/11 attack

• Published in: Social networks 2015-07, Vol.42, p.1-7
• Main Authors: Husslage, Bart, Borm, Peter, Burg, Twan, Hamers, Herbert, Lindelauf, Roy
• Format: Article
• Language: English
• Subjects: Al Qaeda; Centrality; Centrality measures; Coalitions; Cooperative game theory; Decisions; Intelligence; Intelligence services; Network analysis; Prevention; Social Support; Surveillance; Terrorism; Threat
• ISSN: 0378-8733; 1879-2111
• DOI: 10.1016/j.socnet.2015.02.003

•Game theoretic centrality incorporates both network features and non-network features.•Game theoretic centrality leads to new insights about key players in terrorist networks.•Game theoretic centrality leads to robust rankings of terrorists. All over the world, intelligence services are collecting data concerning possible terrorist threats. This information is usually transformed into network structures in which the nodes represent the individuals in the data set and the links possible connections between these individuals. Unfortunately, it is nearly impossible to keep track of all individuals in the resulting complex network. Therefore, Lindelauf et al. (2013) introduced a methodology that ranks terrorists in a network. The rankings that result from this methodology can be used as a decision support system to efficiently allocate the scarce surveillance means of intelligence agencies. Moreover, usage of these rankings can improve the quality of surveillance which can in turn lead to prevention of attacks or destabilization of the networks under surveillance. The methodology introduced by Lindelauf et al. (2013) is based on a game theoretic centrality measure, which is innovative in the sense that it takes into account not only the structure of the network but also individual and coalitional characteristics of the members of the network. In this paper we elaborate on this methodology by introducing a new game theoretic centrality measure that better takes into account the operational strength of connected subnetworks. Moreover, we perform a sensitivity analysis on the rankings derived from this new centrality measure for the case of Al Qaeda's 9/11 attack. In this sensitivity analysis we consider firstly the possible additional information available about members of the network, secondly, variations in relational strength and, finally, the absence or presence of a small percentage of links in the network. We also introduce a case specific method to compare the different rankings that result from the sensitivity analysis and show that the new centrality measure is robust to small changes in the data.