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

Takeshi Kurosawa, Y. Takama
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引用次数: 5

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.
利用可视化系统预测研究人员的未来活动
本文提出了一个可视化系统,用于从合作作者网络中洞察未来的研究活动。共同作者网络和引文网络等文献网络是研究人员进行研究调查时的重要信息。特别是,与研究人员的未来活动有关的研究调查的要求很多,如确定杰出的研究人员,包括成长中的研究人员和导师。尽管引文网络受到了研究者的广泛关注,但由于它反映了研究者过去的活动,因此并不适合此类调查。由于研究人员的合作对研究人员的活动至关重要,合作作者网络适用于预测未来的活动。为了通过区分成长研究领域和成熟研究领域来洞察未来的研究活动,所提出的可视化系统提供了识别研究领域以及识别网络结构和关键字分布的时间变化的功能。作为深入了解未来研究活动的基础,本文侧重于区分成长中的研究人员和主管的任务。通过详细分析两位参与者对InfoVis 2004大赛数据集的分析过程,评价了所提系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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