Name
Abstract | ||
|---|---|---|
The motivation for the study described in this paper is realizing the fact that organizational structure of a group is a key indicator in determining its strengths and weaknesses. A general knowledge of the prevalent models of terrorist organizations leads to a better understanding of their capabilities. Knowledge of the different labels and systems of classification that have been applied to groups and individuals aid us in discarding useless or irrelevant terms, and in understanding the purposes and usefulness of different terminologies. Previous studies in network analysis have mostly dealt with legal networks with transparent structures. Terrorist networks share some features with conventional (real world) networks, but they are harder to identify because they mostly hide their illicit activities. In this paper we describe a novel approach for extracting structural patterns of terrorist networks with the help of social network analysis measures and techniques. We propose a global measure for estimating the degree of organization of social networks; the measure is global in terms of being applied to the whole network as an entity and being extracted from the major well-known SNA measures. The importance of such research comes from the fact that individuals in organized intellectual networks and especially terrorist networks tend to hide their individual rules and thus there is a need to deal with such networks as a whole, discovering the degree of organization and thus its strengths and weaknesses. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ASONAM.2010.84 | ASONAM |
Keywords | Field | DocType |
feature extraction,knowledge acquisition,social networking (online),terrorism,SNA measure,degree of organization,network analysis,organized intellectual network,social network analysis,structural pattern extraction,terrorist network,terrorist organization | Data mining,Social network,Organizational structure,Computer science,Social network analysis,Feature extraction,General knowledge,Network analysis,Strengths and weaknesses,Knowledge acquisition | Conference |
Citations | PageRank | References |
3 | 0.44 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khaled Dawoud | 1 | 3 | 1.11 |
| Reda Alhajj | 2 | 1919 | 205.67 |
| Jon Rokne | 3 | 104 | 15.89 |