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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Dynamic social network analysis of a dark network: Identifying significant facilitators |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Page Range | 40 - 46 |
| Event Title | the 5th IEEE Conference on Intelligence and Security Informatics |
| Event Type | conference |
| Event Location | New Brunswick, New Jersey |
| Event Start Date | May 23 - 2007 |
| Event End Date | May 24 - 2007 |
| Place of Publication | New Brunswick, New Jersey |
| Publisher | IEEE |
| Abstract Text | "Dark Networks" refer to various illegal and covert social networks like criminal and terrorist networks. These networks evolve over time with the formation and dissolution of links to survive control efforts by authorities. Previous studies have shown that the link formation process in such networks is influenced by a set of facilitators. However, there have been few empirical evaluations to determine the significant facilitators. In this study, we used dynamic social network analysis methods to examine several plausible link formation facilitators in a large-scale real-world narcotics network. Multivariate Cox regression showed that mutual acquaintance and vehicle affiliations were significant facilitators in the network under study. These findings provide insights into the link formation processes and the resilience of dark networks. They also can be used to help authorities predict co-offending in future crimes. |
| Digital Object Identifier | 10.1109/ISI.2007.379531 |
| Other Identification Number | merlin-id:6808 |
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