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A General Method for Detecting Community Structures in Complex Networks

  • Vesa KuikkaEmail author
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 881)

Abstract

We present a general method for detecting communities and their sub-structures in a complex network. The novelty of the method is to separate the network model and the community detection model. Network connectivity and influence spreading models are used as examples for network models. Depending on the network model, different communities and sub-structures can be found. We illustrate the results with two empirical network topologies. In these cases the strongest detected communities are very similar for the two network models. We use a community detection method that is based on searching local maxima of an influence measure describing interactions between nodes in a network.

Keywords

Complex networks Community detection Influence spreading model Network connectivity Community influence measure 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Finnish Defence Research AgencyRiihimäkiFinland

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