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. © 2014 Xu Hong-lin et al.
Hong-Lin, X., Han-Bing, Y., Cui-Fang, G., & Ping, Z. (2014). Social network analysis based on network motifs. Journal of Applied Mathematics, 2014. https://doi.org/10.1155/2014/874708