@inbook{bb2ac956c1a247d189ce1ec9761e3d76,
title = "Analyzing and visualizing criminal network dynamics: A case study",
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.",
author = "Jennifer Xu and Byron Marshall and Siddharth Kaza and Hsinchun Chen",
year = "2004",
doi = "10.1007/978-3-540-25952-7_27",
language = "English (US)",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "359--377",
editor = "Hsinchun Chen and Zeng, {Daniel D.} and Reagan Moore and John Leavitt",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}