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  • 标题:Co-Authorship Networks Visualization System for Supporting Survey of Researchers’ Future Activities
  • 本地全文:下载
  • 作者:Kurosawa, Takeshi ; Takama, Yasufumi
  • 期刊名称:Journal of Emerging Technologies in Web Intelligence
  • 印刷版ISSN:1798-0461
  • 出版年度:2012
  • 卷号:4
  • 期号:1
  • 页码:3-14
  • DOI:10.4304/jetwi.4.1.3-14
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要:This paper proposes a visualization system that supports users 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 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 supposed to be 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 functions for identifying research areas as well as 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. It is observed that different analyzing strategies are employed by even the same participant, when available support functions are different. The result indicates participants can successfully utilize the functions in their exploratory analysis process.
  • 关键词:exploratory data analysis;interactive information visualization;temporal trend information;coauthorship networks;graph visualization
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