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    Estimating the Importance of Terrorists in a Terror Network

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    Publication date
    2013
    Author
    Elhajj, Ahmad
    Elsheikh, A.
    Addam, O.
    Alzohbi, M.
    Zarour, O.
    Aksaç, A.
    Öztürk, O.
    Özyer, T.
    Ridley, Mick J.
    Alhajj, R.
    Keyword
    Social network analysis; Terror networks; Data mining; Data analysis; Knowledge discovery; Machine learning
    Peer-Reviewed
    yes
    
    Metadata
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    Abstract
    While criminals may start their activities at individual level, the same is in general not true for terrorists who are mostly organized in well established networks. The effectiveness of a terror network could be realized by watching many factors, including the volume of activities accomplished by its members, the capabilities of its members to hide, and the ability of the network to grow and to maintain its influence even after the loss of some members, even leaders. Social network analysis, data mining and machine learning techniques could play important role in measuring the effectiveness of a network in general and in particular a terror network in support of the work presented in this chapter. We present a framework that employs clustering, frequent pattern mining and some social network analysis measures to determine the effectiveness of a network. The clustering and frequent pattern mining techniques start with the adjacency matrix of the network. For clustering, we utilize entries in the table by considering each row as an object and each column as a feature. Thus features of a network member are his/her direct neighbors. We maintain the weight of links in case of weighted network links. For frequent pattern mining, we consider each row of the adjacency matrix as a transaction and each column as an item. Further, we map entries into a 0/1 scale such that every entry whose value is greater than zero is assigned the value one; entries keep the value zero otherwise. This way we can apply frequent pattern mining algorithms to determine the most influential members in a network as well as the effect of removing some members or even links between members of a network. We also investigate the effect of adding some links between members. The target is to study how the various members in the network change role as the network evolves. This is measured by applying some social network analysis measures on the network at each stage during the development. We report some interesting results related to two benchmark networks: the first is 9/11 and the second is Madrid bombing.
    URI
    http://hdl.handle.net/10454/13601
    Version
    No full-text in the repository
    Citation
    Elhajj A, Elsheikh A, Addam O, Alzohbi M, Zarour O, Aksaç A, Öztürk O, Özyer T, Ridley M and Alhajj R (2013) Estimating the Importance of Terrorists in a Terror Network. In: Özyer T, Erdem Z, Rokne J and Khoury S (eds) Mining Social Networks and Security Informatics. Lecture Notes in Social Networks. Springer, Dordrecht. pp 267-283.
    Link to publisher’s version
    http://dx.doi.org/10.1007/978-94-007-6359-3_14
    Type
    Book chapter
    Collections
    Engineering and Informatics Publications

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