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Investigative Data Mining: Mathematical Models for Analyzing, Visualizing and Destabilizing Terrorist Networks

von Nasrullah Memon

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[1.] Nm/Fragment 033 01 - Diskussion
Zuletzt bearbeitet: 2012-04-21 14:57:29 Hindemith
Fragment, Gesichtet, Koelle et al 2006, KomplettPlagiat, Nm, SMWFragment, Schutzlevel sysop

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KomplettPlagiat
Bearbeiter
Graf Isolan
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Yes.png
Untersuchte Arbeit:
Seite: 33, Zeilen: 1-15
Quelle: Koelle et al 2006
Seite(n): 1 (internet version), Zeilen: right column 26-43
1.5. LIMITATIONS

While traditional SNA has been used to successfully derive insights into a social network, it can be restrictive for a number of reasons. SNA assumes a well-formed social network, but real-world methods of data collection may not ensure that the resulting social network is complete and contains needed data. SNA focuses primarily on the existence of a relationship between nodes in the network, but not on attributes of that relationship or the nodes in the relationship. Furthermore, SNA does not explicitly consider the uncertainty of attributes on nodes or relationships. Finally, graph-theoretic algorithms used in SNA tend to focus on homogenous set of entities and relationships, making it difficult to analyze networks that involve a heterogeneous set of nodes connected by a variety of link types.

1.5.1 Issues in Data Collection [FN 7]

[FN 7] The text in this subsection is partially published in Memon Nasrullah and Larsen Henrik Legind. (2007e)

2. LIMITATIONS OF SOCIAL NETWORK ANALYSIS

While traditional SNA has been used to successfully derive insights into a social network, it can be restrictive for a number of reasons. SNA assumes a well-formed social network, but real-world methods of data collection may not ensure that the resulting social network is complete and contains needed data. SNA focuses primarily on the existence of a relationship between nodes in the network, but not on attributes of that relationship or the nodes in the relationship. Furthermore, SNA does not explicitly consider the uncertainty of attributes on nodes or relationships. Finally, graph-theoretic algorithms used in SNA tend to focus on a homogenous set of entities and relationships, making it difficult to analyze networks that involve a heterogeneous set of nodes connected by a variety of link types.

2.1 ISSUES IN DATA COLLECTION

Anmerkungen

Identical, with the source not being mentioned anywhere in Nm's thesis.

Sichter
(Graf Isolan), Hindemith

[2.] Nm/Fragment 033 15 - Diskussion
Zuletzt bearbeitet: 2012-04-21 21:42:30 Hindemith
Fragment, Gesichtet, KomplettPlagiat, Nm, Ressler 2006, SMWFragment, Schutzlevel sysop

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Graf Isolan
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Yes.png
Untersuchte Arbeit:
Seite: 33, Zeilen: 15-30
Quelle: Ressler 2006
Seite(n): 4, Zeilen: 7-19
1.5.1 Issues in Data Collection[FN 7]

Data collection is difficult for any network analysis because it is hard to create a complete network. It is especially difficult to gain information on terrorist networks. Terrorist organizations do not provide information on their members, and the government rarely allows researchers to use their data. A number of academic researchers focus primarily on data collection on terrorist organizations, analyzing the information through description and straightforward modeling. Valdis Krebs was one of the first to collect data using public sources with his 2001 article in Connections. In this work, Krebs creates a pictorial representation of the al Qaeda network (as shown in Figure 1.4) responsible for 9/11 that shows the many connections between the hijackers of the four airplanes. Similarly, After the Madrid bombing in 2004, Spanish sociologist Jose A. Rodriguez conducted an analysis to map the March 11th terrorist network.

[FN 7] The text in this subsection is partially published in Memon Nasrullah and Larsen Henrik Legind. (2007e)

Data Collectors

Data collection is difficult for any network analysis because it is hard to create a complete network. It is especially difficult to gain information on terrorist networks. Terrorist organizations do not provide information on their members, and the government rarely allows researchers to use their intelligence data. A number of academic researchers focus primarily on data collection on terrorist organizations, analyzing the information through description and straightforward modeling. Valdis Krebs was one of the first to collect data using public sources with his 2001 article in Connections. In this work, Krebs creates a pictorial representation of the al Qaeda network responsible for 9/11 that shows the many ties between the hijackers of the four airplanes. After the Madrid bombing in 2004, Spanish sociologist Jose A. Rodriguez completed an analysis similar to Krebs’ by using public sources to map the March 11th terrorist network.

Anmerkungen

The conference, the proceedings of which "this subsection is partially published" in, was held on 4-6 July 2007. Thus the unnamed source predates (again) the text by Nm. It should also be noticed that the coauthors of the conference paper by Nm are his thesis advisor and the chair of his thesis committee.

Note: in the bibliography there are two entries (2007e): "Memon Nasrullah and Larsen Henrik Legind. (2007e)" as well as "Memon Nasrullah, Hicks David L., and Larsen Henrik Legind (2007e)". Only the latter has common text fragments with the chapter 1.5.1 of the dissertation and therefore it was assumed that in FN 7 this publication was meant.

Sichter
(Graf Isolan), Hindemith


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