Visual analysis of network centralities

Tim Dwyer, Seok Hee Hong, Dirk Koschützki, Falk Schreiber, Kai Xu

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

33 Citations (Scopus)


Centrality analysis determines the importance of vertices in a network based on their connectivity within the network structure. It is a widely used technique to analyse network-structured data. A particularly important task is the comparison of different centrality measures within one network. We present three methods for the exploration and comparison of centrality measures within a network: 3D parallel coordinates, orbit-based comparison and hierarchy-based comparison. There is a common underlying idea to all three methods: for each centrality measure the graph is copied and drawn in a separate 2D plane with vertex position dependent on centrality. These planes are then stacked into the third dimension so that the different centrality measures may be easily compared. Only the details of how centrality is mapped to vertex position are different in each method. For 3D parallel coordinates vertices are placed on vertical lines; for orbit-based comparison vertices are placed on concentric circles and for hierarchy-based comparison vertices are placed on horizontal lines. The second and third solutions make it particularly easy to track changing vertex-centrality values in the context of the underlying network structure. The usability of these methods is demonstrated on biological and social networks.

Original languageEnglish
Title of host publicationInformation Visualisation 2006 - Asia Pacific Symposium on Information Visualisation, APVIS 2006
Number of pages9
Publication statusPublished - 1 Dec 2006
EventAsia Pacific Symposium on Information Visualisation, APVIS 2006 - Tokyo, Japan
Duration: 1 Feb 20063 Feb 2006

Publication series

NameConferences in Research and Practice in Information Technology Series
ISSN (Print)1445-1336


ConferenceAsia Pacific Symposium on Information Visualisation, APVIS 2006


  • Biological networks
  • Centralities
  • Graph drawing
  • Network analysis
  • Social networks
  • Visualisation

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