Tracking modularity in citation networks
Tracking modularity in citation networks
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DOI：
10.1007/s11192-010-0158-z
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发表时间：
2010-01
期刊：
影响因子：
3.9
通讯作者：
Y. Takeda;Y. Kajikawa
中科院分区：
文献类型：
--
作者：
Y. Takeda;Y. Kajikawa
引文网络分析是分析科研结构的有效工具。聚类通常用于可视化科学领域，并检测新兴的研究前沿。虽然我们经常任意设置聚类阈值，但很少有设置适当阈值的指南。通过跟踪引文网络聚类过程中规模和模块度的变化，分析了引文网络聚类的基本过程。我们发现，有三个阶段的引文网络的聚类，这是普遍的，在我们的案例研究。在第一阶段中，在域中形成核心簇。在第二阶段，外围集群形成，而核心集群继续增长。在第三阶段，核心集群再次成长。我们发现最小语料库大小约为100，以确保聚类。当语料规模小于100时，聚类网络结构趋于随机。此外，即使对于规模大于它的语料库，在后期形成的一些聚类的聚类质量是低的。这些结果对引文网络分析的使用者具有基本的指导意义。
Citation network analysis is an effective tool to analyze the structure of scientific research. Clustering is often used to visualize scientific domain and to detect emerging research front there. While we often set arbitrarily clustering threshold, there is few guide to set appropriate threshold. This study analyzed basic process how clustering of citation network proceeds by tracking size and modularity change during clustering. We found that there are three stages in clustering of citation networks and it is universal across our case studies. In the first stage, core clusters in the domain are formed. In the second stage, peripheral clusters are formed, while core clusters continue to grow. In the third stage, core clusters grow again. We found the minimum corpus size around one hundred assuring the clustering. When the corpus size is less than one hundred, clustered network structure tends to be more random. In addition even for the corpus whose size is larger than it, the clustering quality for some clusters formed in the later stage is low. These results give a fundamental guidance to the user of citation network analysis.