Visual exploration of collaboration networks based on graph degeneracy

  • Authors:

  • Christos Giatsidis;Klaus Berberich;Dimitrios M. Thilikos;Michalis Vazirgiannis

  • Affiliations:

  • École Polytechnique, Palaiseau Cedex, France;École Polytechnique, Palaiseau Cedex, France;National & Kapodistrian University of Athens, Athens, Greece;Athens University of Economics, Athens, Greece

  • Venue:
  • Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2012

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Abstract

We demonstrate a system that supports the visual exploration of collaboration networks. The system leverages the notion of fractional cores introduced in earlier work to rank vertices in a collaboration network and filter vertices' neighborhoods. Fractional cores build on the idea of graph degeneracy as captured by the notion of k-cores in graph theory and extend it to undirected edge-weighted graphs. In a co-authorship network, for instance, the fractional core index of an author intuitively reflects the degree of collaboration with equally or higher-ranked authors. Our system has been deployed on a real-world co-authorship network derived from DBLP, demonstrating that the idea of fractional cores can be applied even to large-scale networks. The system provides an easy-to-use interface to query for the fractional core index of an author, to see who the closest equally or higher-ranked co-authors are, and explore the entire co-authorship network in an incremental manner.