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Social Network Analysis Based on Network Motifs

Author

Listed:
  • Xu Hong-lin
  • Yan Han-bing
  • Gao Cui-fang
  • Zhu Ping

Abstract

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.

Suggested Citation

  • Xu Hong-lin & Yan Han-bing & Gao Cui-fang & Zhu Ping, 2014. "Social Network Analysis Based on Network Motifs," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:874708
    DOI: 10.1155/2014/874708
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    References listed on IDEAS

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    1. Daniel Gómez & Enrique González–Arangüena & Conrado Manuel & Guillermo Owen & Mónica Pozo & Martha Saboyá, 2008. "The cohesiveness of subgroups in social networks: A view from game theory," Annals of Operations Research, Springer, vol. 158(1), pages 33-46, February.
    2. Theresa Velden & Asif-ul Haque & Carl Lagoze, 2010. "A new approach to analyzing patterns of collaboration in co-authorship networks: mesoscopic analysis and interpretation," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 219-242, October.
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