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Cooperative game theoretic centrality analysis of terrorist networks: The cases of Jemaah Islamiyah and Al Qaeda

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  • Lindelauf, R.H.A.
  • Hamers, H.J.M.
  • Husslage, B.G.M.

Abstract

The identification of key players in a terrorist organization aids in preventing attacks, the efficient allocation of surveillance measures, and the destabilization of the corresponding network. In this paper, we introduce a game theoretic approach to identify key players in terrorist networks. In particular we use the Shapley value as a measure of importance in cooperative games that are specifically designed to reflect the context of the terrorist organization at hand. The advantage of this approach is that both the structure of the terrorist network, which usually reflects a communication and interaction structure, as well as non-network features, i.e., individual based parameters such as financial means or bomb building skills, can be taken into account. The application of our methodology to the analysis results in rankings of the terrorists in the network. We illustrate our methodology through two case studies: Jemaah Islamiyah’s Bali bombing and Al Qaedas 9/11 attack, which lead to new insights in the operational networks responsible for these attacks.

Suggested Citation

  • Lindelauf, R.H.A. & Hamers, H.J.M. & Husslage, B.G.M., 2013. "Cooperative game theoretic centrality analysis of terrorist networks: The cases of Jemaah Islamiyah and Al Qaeda," European Journal of Operational Research, Elsevier, vol. 229(1), pages 230-238.
  • Handle: RePEc:eee:ejores:v:229:y:2013:i:1:p:230-238
    DOI: 10.1016/j.ejor.2013.02.032
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    1. Gomez, Daniel & Gonzalez-Aranguena, Enrique & Manuel, Conrado & Owen, Guillermo & del Pozo, Monica & Tejada, Juan, 2003. "Centrality and power in social networks: a game theoretic approach," Mathematical Social Sciences, Elsevier, vol. 46(1), pages 27-54, August.
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    6. Flores Díaz, Ramón Jesús & Molina, Elisenda & Tejada, Juan, 2013. "The Shapley group value," DES - Working Papers. Statistics and Econometrics. WS ws133430, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Hu, Fei & Zhao, Shangmei & Bing, Tao & Chang, Yiming, 2017. "Hierarchy in industrial structure: The cases of China and the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 871-882.
    8. Hamers, Herbert & Husslage, Bart & Lindelauf, R. & Campen, Tjeerd, 2016. "A New Approximation Method for the Shapley Value Applied to the WTC 9/11 Terrorist Attack," Other publications TiSEM 8a67b416-1091-4efe-a1a6-7, Tilburg University, School of Economics and Management.
    9. Zenou, Yves, 2014. "Key Players," CEPR Discussion Papers 10277, C.E.P.R. Discussion Papers.
    10. González–Arangüena, Enrique & Manuel, Conrado Miguel & del Pozo, Mónica, 2015. "Values of games with weighted graphs," European Journal of Operational Research, Elsevier, vol. 243(1), pages 248-257.
    11. Gusev, Vasily V., 2021. "Nash-stable coalition partition and potential functions in games with coalition structure," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1180-1188.
    12. László Csató, 2017. "Measuring centrality by a generalization of degree," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 771-790, December.
    13. Nizar Allouch & A. Meca & K. Polotskaya, 2021. "The Bonacich Shapley centrality," Studies in Economics 2106, School of Economics, University of Kent.
    14. Mágó, Mánuel, 2018. "Power values and framing in game theory," Other publications TiSEM e7822a6b-a2db-4ce9-bd08-b, Tilburg University, School of Economics and Management.
    15. Tom C. van der Zanden & Hans L. Bodlaender & Herbert J. M. Hamers, 2023. "Efficiently computing the Shapley value of connectivity games in low-treewidth graphs," Operational Research, Springer, vol. 23(1), pages 1-23, March.
    16. Husslage, B.G.M. & Borm, P.E.M. & Burg, T. & Hamers, H.J.M. & Lindelauf, R., 2014. "Ranking Terrorists in Networks : A Sensitivity Analysis of Al Qaeda’s 9/11 Attack," Other publications TiSEM 191548ed-34ba-4aba-abbf-9, Tilburg University, School of Economics and Management.
    17. Ramón Flores & Elisenda Molina & Juan Tejada, 2019. "Evaluating groups with the generalized Shapley value," 4OR, Springer, vol. 17(2), pages 141-172, June.
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    19. Hamers, Herbert & Husslage, Bart & Lindelauf, R. & Campen, Tjeerd, 2016. "A New Approximation Method for the Shapley Value Applied to the WTC 9/11 Terrorist Attack," Discussion Paper 2016-042, Tilburg University, Center for Economic Research.
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