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Identifying significant facilitators of dark network evolution

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  • Daning Hu
  • Siddharth Kaza
  • Hsinchun Chen

Abstract

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.

Suggested Citation

  • Daning Hu & Siddharth Kaza & Hsinchun Chen, 2009. "Identifying significant facilitators of dark network evolution," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(4), pages 655-665, April.
  • Handle: RePEc:bla:jamist:v:60:y:2009:i:4:p:655-665
    DOI: 10.1002/asi.21008
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    Cited by:

    1. Bernard Quinio & Rolande Marciniak, 2013. "Virtual Social Network Characterization: Reference Framework for a Comparative Analysis," Post-Print hal-01755733, HAL.
    2. Li, Bo & Sun, Duoyong & Bai, Guanghan, 2017. "Empirical research on evolutionary behavior of covert network with preference measurement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 33-43.
    3. Gohar Feroz Khan, 2013. "Social media-based systems: an emerging area of information systems research and practice," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 159-180, April.

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