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Visualization of Ranking Authors Based on Social Networks Analysis and Bibliometrics

机译:基于社交网络分析和文献计量学的排名作者可视化

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It is interesting to rank scientists in a specific field, which would help researchers to know about the research status of the field and gain valuable insight on future technical trends in the field. Our paper visualizes the results of author ranking with the consideration of authors' contribution. In this paper, every author's contribution to his/her field is calculated according to the co-authorship among papers. By extracting the papers and authors information from a field since they started publication, the co-author network are constructed. We also get the clusters partition of those authors by Girvan-Newman algorithm. For conducting detailed experiments to show the visualized our results, we select the field of Intelligent transportation system (ITS) as an example. Since thousands of papers were published by scientists each year in the ITS field, academic co-authorship in this field expands fast. We design our dataset composed by data from four journals in the ITS field to visualize our algorithm.
机译:对特定领域的科学家进行排名很有趣,这将有助于研究人员了解该领域的研究状况并获得对该领域未来技术趋势的宝贵见解。本文通过考虑作者的贡献来形象化作者排名的结果。在本文中,每位作者对他/她领域的贡献是根据论文的共同作者来计算的。通过从他们开始发表以来从某个领域中提取论文和作者信息,就可以构建共同作者网络。我们还通过Girvan-Newman算法获得了这些作者的聚类分区。为了进行详细的实验以直观显示我们的结果,我们以智能交通系统(ITS)领域为例。由于ITS领域的科学家每年发表数千篇论文,因此该领域的学术合著人数迅速增加。我们设计由ITS领域中四本期刊的数据组成的数据集,以可视化我们的算法。

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