Analyzing terrorist networks: A case study of the global salafi jihad network

Jialun Qin, Jennifer J. Xu, Daning Hu, Marc Sageman, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

38 Citations (Scopus)

Abstract

It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science
EditorsP. Kantor, G. Muresan, F. Roberts, D.D. Zeng, F.-Y. Wang, H. Chen, R.C. Merkle
Pages287-304
Number of pages18
Volume3495
StatePublished - 2005
EventIEEE International Conference on Intelligence and Security Informatics, ISI 2005 - Atlanta, GA, United States
Duration: May 19 2005May 20 2005

Other

OtherIEEE International Conference on Intelligence and Security Informatics, ISI 2005
CountryUnited States
CityAtlanta, GA
Period5/19/055/20/05

Fingerprint

Electric network analysis
Terrorism
Reinforcement

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

Qin, J., Xu, J. J., Hu, D., Sageman, M., & Chen, H. (2005). Analyzing terrorist networks: A case study of the global salafi jihad network. In P. Kantor, G. Muresan, F. Roberts, D. D. Zeng, F-Y. Wang, H. Chen, & R. C. Merkle (Eds.), Lecture Notes in Computer Science (Vol. 3495, pp. 287-304)

Analyzing terrorist networks : A case study of the global salafi jihad network. / Qin, Jialun; Xu, Jennifer J.; Hu, Daning; Sageman, Marc; Chen, Hsinchun.

Lecture Notes in Computer Science. ed. / P. Kantor; G. Muresan; F. Roberts; D.D. Zeng; F.-Y. Wang; H. Chen; R.C. Merkle. Vol. 3495 2005. p. 287-304.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Qin, J, Xu, JJ, Hu, D, Sageman, M & Chen, H 2005, Analyzing terrorist networks: A case study of the global salafi jihad network. in P Kantor, G Muresan, F Roberts, DD Zeng, F-Y Wang, H Chen & RC Merkle (eds), Lecture Notes in Computer Science. vol. 3495, pp. 287-304, IEEE International Conference on Intelligence and Security Informatics, ISI 2005, Atlanta, GA, United States, 5/19/05.
Qin J, Xu JJ, Hu D, Sageman M, Chen H. Analyzing terrorist networks: A case study of the global salafi jihad network. In Kantor P, Muresan G, Roberts F, Zeng DD, Wang F-Y, Chen H, Merkle RC, editors, Lecture Notes in Computer Science. Vol. 3495. 2005. p. 287-304
Qin, Jialun ; Xu, Jennifer J. ; Hu, Daning ; Sageman, Marc ; Chen, Hsinchun. / Analyzing terrorist networks : A case study of the global salafi jihad network. Lecture Notes in Computer Science. editor / P. Kantor ; G. Muresan ; F. Roberts ; D.D. Zeng ; F.-Y. Wang ; H. Chen ; R.C. Merkle. Vol. 3495 2005. pp. 287-304
@inproceedings{d3c7551f70b6463db10302ca6e56dd93,
title = "Analyzing terrorist networks: A case study of the global salafi jihad network",
abstract = "It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.",
author = "Jialun Qin and Xu, {Jennifer J.} and Daning Hu and Marc Sageman and Hsinchun Chen",
year = "2005",
language = "English (US)",
volume = "3495",
pages = "287--304",
editor = "P. Kantor and G. Muresan and F. Roberts and D.D. Zeng and F.-Y. Wang and H. Chen and R.C. Merkle",
booktitle = "Lecture Notes in Computer Science",

}

TY - GEN

T1 - Analyzing terrorist networks

T2 - A case study of the global salafi jihad network

AU - Qin, Jialun

AU - Xu, Jennifer J.

AU - Hu, Daning

AU - Sageman, Marc

AU - Chen, Hsinchun

PY - 2005

Y1 - 2005

N2 - It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.

AB - It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.

UR - http://www.scopus.com/inward/record.url?scp=24944475288&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=24944475288&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:24944475288

VL - 3495

SP - 287

EP - 304

BT - Lecture Notes in Computer Science

A2 - Kantor, P.

A2 - Muresan, G.

A2 - Roberts, F.

A2 - Zeng, D.D.

A2 - Wang, F.-Y.

A2 - Chen, H.

A2 - Merkle, R.C.

ER -