Detection method of emerging leading papers using time transition
Detection method of emerging leading papers using time transition
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DOI：
10.1007/s11192-014-1380-x
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发表时间：
2014-07
期刊：
影响因子：
3.9
通讯作者：
S. Iwami;Junichiro Mori;I. Sakata;Y. Kajikawa
中科院分区：
文献类型：
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作者：
S. Iwami;Junichiro Mori;I. Sakata;Y. Kajikawa
为了在当今信息快速增长的世界范围内的研发竞争中生存下来，决策者和研究人员需要得到支持，找到有前途的研究领域和论文。但是，在海量的信息中从可用的数据中找到这些字段变得困难。我们的目标是开发一种方法，支持用文献计量学的方法寻找新兴的领先论文。本文使用我们的时间转换分析方法对四个学术领域进行分析。在时间变迁分析中，在构建引文网络后，计算每篇论文的中心度并跟踪它们的变化。然后，绘制中心点图，提取主要论文的特征。基于这些特征，我们提出了通过关注中心度及其转换来检测前导论文的方法。这项工作将有助于找到领先的论文，并有助于决策者和研究人员决定有价值的研究课题来投入他们的资源。
To survive worldwide competitions of research and development in the current rapid increase of information, decision-makers and researchers need to be supported to find promising research fields and papers. But finding those fields from an available data in too much heavy flood of information becomes difficult. We aim to develop a methodology supporting to find emerging leading papers with a bibliometric approach. The analyses in this work are about four academic domains using our time transition analysis. In the time transition analysis, after citation networks are constructed, centralities of each paper are calculated and their changes are tracked. Then, the centralities are plotted, and the features of the leading papers are extracted. Based on the features, we proposed ways to detect the leading papers by focusing on in-degree centrality and its transition. This work will contribute to finding the leading paper, and it is useful for decision-makers and researchers to decide the worthy research topic to invest their resources.