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| [1.] Nm/Fragment 080 01 - Diskussion Zuletzt bearbeitet: 2012-04-20 22:04:52 WiseWoman | Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung, Xu etal 2004 |
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| Untersuchte Arbeit: Seite: 80, Zeilen: 1-29 |
Quelle: Xu etal 2004 Seite(n): 3-4, Zeilen: 3:14ff; 4:11-22 |
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| There have been some empirical studies that have used SNA methods to analyze criminal or terrorist networks. For instance, based on archival data, Baker and Faulkner analyzed the structure of an illegal network depicting a price-fixing conspiracy in the heavy electrical equipment industry. Their findings supported that individual centrality in the network, as measured by degree, betweenness, and closeness (Freeman, L.C., 1979), was an important forecaster of an individual’s possible prosecution (Baker, W.E. and R.R. Faulkner 1993). Krebs analysed the open source data and studied the terrorist network involved in 9/11 terrorist plot. He found that Mohamed Atta, who piloted the first plane that crashed into the World Trade Center, had the highest degree and acted as the ring leader of the network (Krebs, V., 2002). Xu and Chen employed clustering, centrality measures, block-modeling,and multidimensional scaling (MDS) approaches from SNA to study criminal networks based on crime incident data (Xu, J. & H. Chen, 2003). The system they developed can also visualize a network and its groups.
In the following section we review related SNA research about dynamic network analysis and visualization. 2.13 ANALYZING SOCIAL NETWORK DYNAMICS Recently, the attention on research on social network dynamics has increased. However, there has not been a consensus on what analytical methods to use (Carley, K.M., et al., 2003; Doreian, P., et al., 1997; Nakao, K. and A.K. Romney, 1993). Research uses various methods, measures, models, and techniques to studynetwork dynamics. Doreian and Stokman classified existing approaches into three categories: descriptive, statistical, andsimulation methods (Doreian, P. and F.N. Stokman, 1997). |
There have been some empirical studies that use SNA methods to analyze criminal or terrorist networks. For instance, based on archival data, Baker and Faulkner analyzed the structure of an illegal network depicting a price-fixing conspiracy in the heavy electrical equipment industry. They find that individual centrality in the network, as measured by degree, betweenness, and closeness [EN 17], is an important predictor of an individual’s possible prosecution [EN 1]. Krebs relied on open source data and studied the terrorist network centering around the 19 hijackers in 9/11 events. He found that Mohamed Atta, who piloted the first plane that crashed into the World Trade Center, had the highest degree and acted as the ring leader of the network [EN 23]. Xu and Chen employed clustering, centrality measures, blockmodeling, and
[P. 4] multidimensional scaling (MDS) approaches from SNA to study criminal networks based on crime incident data [EN 41]. The system they developed can also visualize a network and its groups. [...] 3. Literature Review In this section we review related SNA research about dynamic network analysis and visualization. 3.1 Analyzing social network dynamics Recently, the research on social network dynamics has received increasing attention. However, there has not been a consensus on what analytical methods to use [EN 4, EN 14, EN 27]. Research uses various methods, measures, models, and techniques to study network dynamics. Doreian and Stokman classified existing approaches into three categories: descriptive, statistical, and simulation methods [EN 15]. [Pp. 27-29] [EN 1] Baker, W.E. & R.R. Faulkner (1993) The social organization of conspiracy: Illegal networks in the heavy electrical equipment industry. American Sociological Review, 58(12), 837-860. [EN 4] Carley, K.M., et al. (2003) Destabilizing dynamic covert networks. In Proceedings of the 8th International Command and Control Research and Technology Symposium. Washington DC., VA. [EN 14] Doreian, P., et al. (1997) A brief history of balance through time, in Evolution of social networks, P. Doreian & F.N. Stokman (eds.). Gordon and Breach: Australia. 129-147. [EN 15] Doreian, P. & F.N. Stokman (1997) The dynamics and evolution of social networks, in Evolution of social networks, P. Doreian & F.N. Stokman (eds.). Gordon and Breach: Australia. 1-17. [EN 17] Freeman, L.C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1, 215-240. [EN 23] Krebs, V.E. (2001). Mapping networks of terrorist cells. Connections, 24(3), 43-52. [EN 27] Nakao, K. & A.K. Romney (1993) Longitudinal approach to subgroup formation: Re-analysis of Newcomb's fraternity data. Social Networks, 15, 109-131. [EN 41] Xu, J. & H. Chen (2003). Untangling criminal networks: A case study. In Proceedings of NSF/NIJ Symposium on Intelligence and Security Informatics (ISI'03) Tucson, AZ. |
Source is not given. The text has been copied with only minor adjustments -- also all literature references have been copied. |
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