The European Physical Journal B

, Volume 38, Issue 2, pp 305–309 | Cite as

Multi-component static model for social networks

  • D.-H. Kim
  • B. KahngEmail author
  • D. Kim


The static model was introduced to generate a scale-free network. In the model, N number of vertices are present from the beginning. Each vertex has its own weight, representing how much the vertex is influential in a system. The static model, however, is not relevant, when a complex network is composed of many modules such as communities in social networks. An individual may belong to more than one community and has distinct weights for each community. Thus, we generalize the static model by assigning a q-component weight on each vertex. We first choose a component \((\mu)\) among the q components at random and a pair of vertices is linked with a color μ according to their weights of the component \((\mu)\) as in the static model. A (1-f) fraction of the entire edges is connected following this way. The remaining fraction f is added with (q + 1)-th color as in the static model but using the maximum weights among the q components each individual has. The social activity with such maximum weights is an essential ingredient to enhance the assortativity coefficient as large as the ones of real social networks.


Color Social Network Static Model Social Activity Complex Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin/Heidelberg 2004

Authors and Affiliations

  1. 1.School of Physics and Center for Theoretical PhysicsSeoul National UniversitySeoulKorea

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