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DenGraph-HO: Density-based Hierarchical Community Detection for Explorative Visual Network Analysis

  • Nico SchlitterEmail author
  • Tanja Falkowski
  • J¨org L¨assig
Conference paper

Abstract

For the analysis of communities in social networks several data mining techniques have been developed such as the DenGraph algorithm to study the dynamics of groups in graph structures. The here proposed DenGraph-HO algorithm is an extension of the density-based graph clusterer DenGraph. It produces a cluster hierarchy that can be used to implement a zooming operation for visual social network analysis. The clusterings in the hierarchy fulfill the DenGraph-O paradigms and can be efficiently computed. We apply DenGraph-HO on a data set obtained from the music platform Last.fm and demonstrate its usability.

Keywords

Social Network Analysis Community Detection Core Node Community Detection Algorithm Border Node 
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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Notes

Acknowledgements

This work was supported by the members of the distributedDataMining BOINC [1] project (http://www.distributedDataMining.org).

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Nico Schlitter
    • 1
    Email author
  • Tanja Falkowski
    • 2
  • J¨org L¨assig
    • 1
  1. 1.University of Applied Sciences Zittau/Görlitz, Group for Enterprise Application DevelopmentGörlitzGermany
  2. 2.University of Göttingen, Göttingen InternationalGöttingenGermany

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