Christos Giatsidis
Klaus Berberich
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.
- V. Batagelj and M. Zaversnik. An o(m) algorithm for cores decomposition of networks. CoRR, cs.DS/0310049, 2003.Google Scholar
- B. Bollobás. The evolution of sparse graphs. In Graph theory and combinatorics (Cambridge, 1983), pages 35--57. Academic Press, London, 1984.Google Scholar
- L. Egghe. Theory and practise of the g-index. Scientometrics, 69(1):131--152, 2006.Google ScholarCross Ref
- P. Erdős. On the structure of linear graphs. Israel J. Math., 1:156--160, 1963.Google ScholarCross Ref
- P. Erdős and A. Rényi. On the evolution of random graphs. Magyar Tud. Akad. Mat. Kutató Int. Közl., 5:17--61, 1960.Google Scholar
- C. Giatsidis, D. M. Thilikos, and M. Vazirgiannis. Evaluating cooperation in communities with the k-core structure. In ASONAM, pages 87--93, 2011. Google ScholarDigital Library
- J. Hirsch. An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United states of America, 102(46):16569, 2005.Google ScholarCross Ref
- D. W. Matula. A min--max theorem for graphs with application to graph coloring. SIAM Reviews, 10:481--482, 1968.Google Scholar
- B. Pittel, J. Spencer, and N. Wormald. Sudden emergence of a giant k-core in a random graph. J. Combin. Theory Ser. B, 67(1):111--151, 1996. Google ScholarDigital Library
- G. Szekeres and H. S. Wilf. An inequality for the chromatic number of a graph. J. Combinatorial Theory, 4:1--3, 1968.Google ScholarCross Ref
- T. Auczak. Size and connectivity of the k-core of a random graph. Discrete Mathematics, pages 61--68, 1991. Google ScholarDigital Library
Index Terms
- Visual exploration of collaboration networks based on graph degeneracy
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