Analyzing and visualizing criminal network dynamics: A case study

Jennifer Xu, Byron Marshall, Siddharth Kaza, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingChapter

29 Scopus citations

Abstract

Dynamic criminal network analysis is important for national security but also very challenging. However, little research has been done in this area. In this paper we propose to use several descriptive measures from social network analysis research to help detect and describe changes in criminal organizations. These measures include centrality for individuals, and density, cohesion, and stability for groups. We also employ visualization and animation methods to present the evolution process of criminal networks. We conducted a field study with several domain experts to validate our findings from the analysis of the dynamics of a narcotics network. The feedback from our domain experts showed that our approaches and the prototype system could be very helpful for capturing the dynamics of criminal organizations and assisting crime investigation and criminal prosecution.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsHsinchun Chen, Daniel D. Zeng, Reagan Moore, John Leavitt
PublisherSpringer-Verlag
Pages359-377
Number of pages19
ISBN (Electronic)9783540221258
DOIs
StatePublished - Jan 1 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3073
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Xu, J., Marshall, B., Kaza, S., & Chen, H. (2004). Analyzing and visualizing criminal network dynamics: A case study. In H. Chen, D. D. Zeng, R. Moore, & J. Leavitt (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 359-377). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3073). Springer-Verlag. https://doi.org/10.1007/978-3-540-25952-7_27