Visualizing criminal relationships: comparison of a hyperbolic tree and a hierarchical list

  • Authors:

  • Yang Xiang;Michael Chau;Homa Atabakhsh;Hsinchun Chen

  • Affiliations:

  • Department of Management Information Systems, Eller College of Business and Public Administration, The University of Arizona, Tucson, Arizona;School of Business, Faculty of Business and Economics, The University of Hong Kong, Pokfulam, Hong Kong;Department of Management Information Systems, Eller College of Business and Public Administration, The University of Arizona, Tucson, Arizona;Department of Management Information Systems, Eller College of Business and Public Administration, The University of Arizona, Tucson, Arizona

  • Venue:
  • Decision Support Systems
  • Year:
  • 2005

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Abstract

In crime analysis, law enforcement officials have to process a large amount of criminal data and figure out their relationships. It is important to identify different associations among criminal entities. In this paper, we propose the use of a hyperbolic tree view and a hierarchical list view to visualize criminal relationships. A prototype system called COPLINK Criminal Relationship Visualizer was developed. An experiment was conducted to test the effectiveness and the efficiency of the two views. The results show that the hyperbolic tree view is more effective for an "identify" task and more efficient for an "associate" task. The participants generally thought it was easier to use the hierarchical list, with which they were more familiar. When asked about the usefulness of the two views, about half of the participants thought that the hyperbolic tree was more useful, while the other half thought otherwise. Our results indicate that both views can help in criminal relationship visualization. While the hyperbolic tree view performs better in some tasks, the users' experiences and preferences will impact the decision on choosing the visualization technique.