• DocumentCode
    1608298
  • Title

    Predicting Researchers´ Future Activities Using Visualization System for Co-authorship Networks

  • Author

    Kurosawa, Takeshi ; Takama, Yasufumi

  • Author_Institution
    Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Tokyo, Japan
  • Volume
    1
  • fYear
    2011
  • Firstpage
    332
  • Lastpage
    339
  • Abstract
    This paper proposes a visualization system for getting insight into future research activities from co-authorship networks. A bibliographic network such as a co-authorship network and a citation network is important information for researchers when doing a research survey. In particular, there are many requests on research survey that relate with researchers´ future activities, such as identification of remarkable of researchers including growing researchers and supervisors. Although a citation network has received many attentions from researchers, it is not suitable for such surveys because it reflects researchers´ past activities. Since collaboration of researchers is essential for researchers´ activities, co-authorship network is suitable for predicting future activities. In order to get insights into future research activities by discriminating growing research areas from grown-up areas, the proposed visualization system provides the function for identifying research areas and that for identifying time variation of both network structure and keyword distribution. As a basis for getting insights into future research activities, this paper focuses on the task of discriminating growing researchers from supervisors. The effectiveness of the proposed system is evaluated through the detailed analysis of two participants´ analyzing process of InfoVis 2004 Contest dataset.
  • Keywords
    bibliographic systems; citation analysis; data visualisation; groupware; InfoVis 2004 Contest dataset; bibliographic network; citation network; co-authorship networks; keyword distribution; network structure; researcher collaboration; researcher future activities prediction; researcher remarkable identification; visualization system; Brightness; Collaboration; Color; Data visualization; Educational institutions; System analysis and design; Visualization; co-authorship networks; exploratory data analysis; graph visualization; interactive information visualization; temporal trend information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Lyon
  • Print_ISBN
    978-1-4577-1373-6
  • Electronic_ISBN
    978-0-7695-4513-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2011.96
  • Filename
    6038703