• DocumentCode
    721368
  • Title

    MultiStory: Visual analytics of dynamic multi-relational networks

  • Author

    Meidiana, Amyra ; Seok-Hee Hong

  • Author_Institution
    Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2015
  • fDate
    14-17 April 2015
  • Firstpage
    75
  • Lastpage
    79
  • Abstract
    Modern-day social networks are often dynamic and multi-relational, however there is currently little being studied on how to incorporate both aspects simultaneously to support visual analytic tasks for such complex social networks. We present a visual analytic framework for dynamic multi-relational networks and a prototype implementation, called the MultiStory system, which includes two new visualisation methods, AlterCluster and InterArc, designed for dynamic networks with multiple relations. The system is evaluated with two case studies using social networks from the MIT Reality Commons to demonstrate the effectiveness of the system to support a variety of visual analytical tasks on dynamic multi-relational networks.
  • Keywords
    complex networks; data analysis; data visualisation; graph theory; mathematics computing; network theory (graphs); AlterCluster; InterArc; MultiStory system; complex social network; dynamic multirelational network; visual analytics; Blogs; Communities; Data visualization; Marine vehicles; Social network services; Visual analytics; Graph/Network Data; Time Series Data; Visual Knowledge Discovery; Visualization in Social and Information Sciences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization Symposium (PacificVis), 2015 IEEE Pacific
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/PACIFICVIS.2015.7156359
  • Filename
    7156359