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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Identifying significant facilitators of dark network evolution
Organization Unit
Authors
  • Daning Hu
  • Siddharth Kaza
  • Hsinchun Chen
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Journal of the American Society for Information Science and Technology
Publisher Wiley-Blackwell / American Society for Information Science and Technology
Geographical Reach international
ISSN 0002-8231
Volume 60
Number 4
Page Range 655 - 665
Date 2009
Abstract Text Social networks evolve over time with the addition and removal of nodes and links to survive and thrive in their environments. 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 important facilitators. In a research partnership with law enforcement agencies, we used dynamic social-network analysis methods to examine several plausible facilitators of co-offending relationships in a large-scale narcotics network consisting of individuals and vehicles. Multivariate Cox regression and a two-proportion z-test on cyclic and focal closures of the network showed that mutual acquaintance and vehicle affiliations were significant facilitators for the network under study. We also found that homophily with respect to age, race, and gender were not good predictors of future link formation in these networks. Moreover, we examined the social causes and policy implications for the significance and insignificance of various facilitators including common jails on future co-offending. These findings provide important insights into the link-formation processes and the resilience of social networks. In addition, they can be used to aid in the prediction of future links. The methods described can also help in understanding the driving forces behind the formation and evolution of social networks facilitated by mobile and Web technologies.
Digital Object Identifier 10.1002/asi.21008
Other Identification Number merlin-id:6374
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Keywords Human-Computer Interaction, Computer Networks and Communications, Software, Artificial Intelligence, Information Systems