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Co-Authorship Networks Visualization System for Supporting Survey of Researchers’ Future Activities

机译:共同作者网络可视化系统,用于支持研究人员未来活动的调查

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—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.
机译:—本文提出了一种可视化系统,该系统支持用户从共同作者网络深入了解未来的研究活动。诸如合著者网络和引文网络之类的书目网络对于研究人员在进行研究调查时是重要的信息。特别是,研究调查中有许多与研究人员未来活动相关的要求,例如确定杰出的研究人员,包括成长中的研究人员和主管。尽管引文网络已引起研究人员的广泛关注,但由于它反映了研究人员的过去活动,因此不适合进行此类调查。由于研究人员的协作对于研究人员的活动至关重要,因此合著者网络应该适合预测未来的活动。为了通过区分成长中的研究领域和成长中的领域来获得对未来研究活动的见识,所提出的可视化系统提供了用于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,本文着重于将成长中的研究人员与主管区分开来的任务。通过对两位参与者的InfoVis 2004竞赛数据集的分析过程进行详细分析,评估了所提出系统的有效性。可以观察到,当可用的支持功能不同时,即使是同一参与者也采用了不同的分析策略。结果表明参与者可以在其探索性分析过程中成功利用这些功能。

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