Social Network Analysis Based on Network Motifs

被引:4
作者
Xu Hong-lin [1 ]
Yan Han-bing [1 ]
Gao Cui-fang [1 ]
Zhu Ping [1 ]
机构
[1] Jiangnan Univ, Sch Sci, Wuxi 214122, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
DYNAMICS;
D O I
10.1155/2014/874708
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. In application analysis, our approach is shown to be effective.
引用
收藏
页数:6
相关论文
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