Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications
Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications
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DOI：
10.1016/j.techfore.2010.07.006
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发表时间：
2011-02-01
影响因子：
12
通讯作者：
Matsushima, Katsumori
中科院分区：
文献类型：
--
作者：
Shibata, Naoki;Kajikawa, Yuya;Matsushima, Katsumori
在本文中，我们在大量与再生医学相关的学术论文中发现了新兴的研究前沿，再生医学是一个根本性创新研究领域。我们使用拓扑聚类方法将引文网络划分为簇，跟踪每个簇中论文的位置，并使用每个簇的特征术语可视化引文网络。通过平均发表年份和每个聚类的亲子关系来分析聚类结果可能有助于检测最近的趋势。此外，跟踪拓扑度量、簇内度 z 和参与系数 P. 使我们能够确定是否存在新兴知识簇。我们的结果表明我们的方法在发现再生医学新兴研究前沿方面取得了成功，并且这些结果被专家证实是合理的。最后，我们通过成体干细胞和成体干细胞研究的引用网络中的介数中心来预测未来的核心论文，以及可能被多次引用的论文。 (C) 2010 Elsevier Inc. 保留所有权利。
In this paper, we detect emerging research fronts in a huge number of academic papers related to regenerative medicine, a field of radically innovative research. We divide citation networks into clusters using the topological clustering method, track the positions of papers in each cluster, and visualize citation networks with characteristic terms for each cluster. Analyzing the clustering results with the average published year and parent-child relationship of each cluster could be helpful in detecting recent trends. In addition, tracking topological measures, within-cluster degree z and participation coefficient P. enables us to determine whether there are emerging knowledge clusters. Our results show the success of our method in detecting emerging research fronts in regenerative medicine, and these results are confirmed as reasonable by experts. Finally, we predict the future core papers, with the potential of many citations, via the betweenness centralities in the citation network of the research into adult and somatic stem cells. (C) 2010 Elsevier Inc. All rights reserved.