On the visualization of social and other scale-free networks

Yuntao Jia, Jared Hoberock, Michael Garland, John C. Hart

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number4658141
Pages (from-to)1285-1292
Number of pages8
JournalIEEE Transactions on Visualization and Computer Graphics
Volume14
Issue number6
DOIs
StatePublished - Nov 1 2008

Keywords

  • Anisotropic shading
  • Betweenness centrality
  • Edge filtering
  • Scale-free network

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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