• DocumentCode
    38576
  • Title

    A Task Taxonomy for Network Evolution Analysis

  • Author

    Jae-wook Ahn ; Plaisant, Catherine ; Shneiderman, Ben

  • Author_Institution
    Human Comput. Interaction Lab. (HCIL), Univ. of Maryland, College Park, MD, USA
  • Volume
    20
  • Issue
    3
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    365
  • Lastpage
    376
  • Abstract
    Visualization has proven to be a useful tool for understanding network structures. Yet the dynamic nature of social media networks requires powerful visualization techniques that go beyond static network diagrams. To provide strong temporal network visualization tools, designers need to understand what tasks the users have to accomplish. This paper describes a taxonomy of temporal network visualization tasks. We identify the 1) entities, 2) properties, and 3) temporal features, which were extracted by surveying 53 existing temporal network visualization systems. By building and examining the task taxonomy, we report which tasks are well covered by existing systems and make suggestions for designing future visualization tools. The feedback from 12 network analysts helped refine the taxonomy.
  • Keywords
    data visualisation; evolutionary computation; social networking (online); data visualisation; network evolution analysis; network structures; social media networks; static network diagrams; task taxonomy; temporal network visualization systems; temporal network visualization tools; visualization techniques; Communities; Compounds; Data visualization; Evolution (biology); Social network services; Taxonomy; Visualization; Network visualization; design space; network evolution; task taxonomy; temporal analysis;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2013.238
  • Filename
    6620874