• DocumentCode
    756503
  • Title

    Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction

  • Author

    Shen, Z. ; Ma, K.-L. ; Eliassi-Rad, Tina

  • Author_Institution
    Div. of Comput. Sci., California Univ., Davis, CA
  • Volume
    12
  • Issue
    6
  • fYear
    2006
  • Firstpage
    1427
  • Lastpage
    1439
  • Abstract
    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
  • Keywords
    data visualisation; inference mechanisms; ontologies (artificial intelligence); social sciences computing; analytic reasoning; graph drawing; heterogeneous social network; importance filtering; information visualization; ontology; semantic-structural abstraction; sociology; visual analytics tool; Graph drawing; information visualization; ontology; semantic graphs; social networks; visual analytics.; Algorithms; Computer Graphics; Computer Simulation; Information Storage and Retrieval; Semantics; Social Support; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2006.107
  • Filename
    1703364