Centrality Based Visualization of Small World Graphs

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dc.contributor.authorHam, Frank vanen_US
dc.contributor.authorWattenberg, Martinen_US
dc.contributor.editorA. Vilanova, A. Telea, G. Scheuermann, and T. Moelleren_US
dc.date.accessioned2014-02-21T18:45:14Z
dc.date.available2014-02-21T18:45:14Z
dc.date.issued2008en_US
dc.description.abstractCurrent graph drawing algorithms enable the creation of two dimensional node-link diagrams of huge graphs. However, for graphs with low diameter (of which "small world" graphs are a subset) these techniques begin to break down visually even when the graph has only a few hundred nodes. Typical algorithms produce images where nodes clump together in the center of the screen, making it hard to discern structure and follow paths. This paper describes a solution to this problem, which uses a global edge metric to determine a subset of edges that capture the graph's intrinsic clustering structure. This structure is then used to create an embedding of the graph, after which the remaining edges are added back in. We demonstrate applications of this technique to a number of real world examples.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume27en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2008.01232.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleCentrality Based Visualization of Small World Graphsen_US
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27-Issue 3
EuroVis08: Joint Eurographics - IEEE VGTC Symposium on Visualization