Visual analysis of large heterogeneous social networks by semantic and structural abstraction

Zeqian Shen, Kwan-Liu Ma, Tina Eliassi-Rad

Research output: Contribution to journalArticlepeer-review

140 Scopus citations


Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema), OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

Original languageEnglish (US)
Article number1703364
Pages (from-to)1427-1439
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number6
StatePublished - Nov 1 2006


  • Graph drawing
  • Information visualization
  • Ontology
  • Semantic graphs
  • Social networks
  • Visual analytics

ASJC Scopus subject areas

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


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