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Title:Visualization of Social and other Scale-Free Networks
Author(s):Jia, Yuntao; Hoberock, Jared; Garland, Michael; Hart, John C.
Subject(s):networking
computer graphics
Abstract:This paper proposes novel methods for visualizing specifically the large power-law graphs that arise in sociology and the sciences. In such cases a large portion of edges can be shown to be less important and removed while preserving component connectedness and other features (e.g. cliques) to more clearly reveal the network's underlying connection pathways. This simplification approach deterministically filters (instead of clustering) the graph to retain important node and edge semantics, and works both automatically and interactively. The improved graph filtering and layout is combined with a novel computer graphics anisotropic shading of the dense crisscrossing array of edges to yield a full social network and scale-free graph visualization system. Both quantitative analysis and visual results demonstrate the effectiveness of this approach.
Issue Date:2008-04
Genre:Technical Report
Type:Text
URI:http://hdl.handle.net/2142/11447
Other Identifier(s):UIUCDCS-R-2008-2955
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-22


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