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The Weak Core and the Structure of Elites in Social Multiplex Networks

  • Bernat Corominas-MurtraEmail author
  • Stefan Thurner
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Recent approaches on elite identification highlighted the important role of intermediaries, by means of a new definition of the core of a multiplex network, the generalised K-core. This newly introduced core subgraph crucially incorporates those individuals who, in spite of not being very connected, maintain the cohesiveness and plasticity of the core. Interestingly, it has been shown that the performance on elite identification of the generalised K-core is sensibly better that the standard K-core. Here we go further: Over a multiplex social system, we isolate the community structure of the generalised K-core and we identify the weakly connected regions acting as bridges between core communities, ensuring the cohesiveness and connectivity of the core region. This gluing region is the Weak core of the multiplex system. We test the suitability of our method on data from the society of 420,000 players of the Massive Multiplayer Online Game Pardus. Results show that the generalised K-core displays a clearly identifiable community structure and that the weak core gluing the core communities shows very low connectivity and clustering. Nonetheless, despite its low connectivity, the weak core forms a unique, cohesive structure. In addition, we find that members populating the weak core have the best scores on social performance, when compared to the other elements of the generalised K-core. The weak core provides a new angle on understanding the social structure of elites, highlighting those subgroups of individuals whose role is to glue different communities in the core.

Keywords

Weak Core Multiplex Networks (MPN) Multiplex Social System Coral Communities Core Subgraph 
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.

Notes

Acknowledgements

This work was supported by the Austrian Science Fund FWF under KPP23378FW, the EU LASAGNE project, no. 318132 and the EU MULTIPLEX project, no. 318132.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Section for Science of Complex SystemsMedical University of ViennaViennaAustria
  2. 2.Santa Fe InstituteSanta FeUSA
  3. 3.IIASALaxenburgAustria

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