Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports
Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports
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DOI：
10.1108/00220410410548144
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发表时间：
2004-01-01
影响因子：
2.1
通讯作者：
Leydesdorff, L
中科院分区：
文献类型：
--
作者：
Leydesdorff, L
从2001年的期刊引文报告得出的聚合期刊-期刊引文矩阵，可以分解成一个独特的主题分类使用双连通组件的图形分析算法。这项技术最近被纳入社交网络分析的软件工具中。可以使用表明各组成部分之间重叠的连接点，根据其可分解性评估矩阵。这一组的衔接点并没有表现出一个下一级网络的“一般科学”期刊。然而，集群的大小和内部密度不同的关系。期刊的完整分类见附录。还可以提取和映射聚类以进行可视化。
The aggregate journal-journal citation matrix derived from Journal Citation Reports 2001 can be decomposed into a unique subject classification using the graph-analytical algorithm of bi-connected components. This technique was recently incorporated in software tools for social network analysis. The matrix can be assessed in terms of its decomposability using articulation points which indicate overlap between the components. The articulation points of this set did not exhibit a next-order network of "general science" journals. However, the clusters differ in size and in terms of the internal density of their relations. A full classification of the journals is provided in the Appendix. The clusters can also be extracted and mapped for the visualization.