On Spectral Partitioning of Co-authorship Networks

  • Václav Snášel
  • Pavel Krömer
  • Jan Platoš
  • Miloš Kudělka
  • Zdeněk Horák
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7564)

Abstract

Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we explore two community detection approaches based on the spectral partitioning to analyze a co-authorship network. The partitioning exploits the concepts of algebraic connectivity and characteristic valuation to form components useful for the analysis of relations and communities in real world social networks.

Keywords

spectral partitioning algebraic connectivity co-authorship DBLP 

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Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Václav Snášel
    • 1
  • Pavel Krömer
    • 1
  • Jan Platoš
    • 1
  • Miloš Kudělka
    • 1
  • Zdeněk Horák
    • 1
  1. 1.Department of Computer ScienceVŠB-Technical University of OstravaOstrava-PorubaCzech Republic

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