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

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


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 and demonstrate its usability.


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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This work was supported by the members of the distributedDataMining BOINC [1] project (

References 22

  1. 1.
    Anderson, D.P.: Boinc: A system for public-resource computing and storage. In: Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing, GRID ’04, pp. 4–10. IEEE Computer Society, Washington, DC, USA (2004)Google Scholar
  2. 2.
    Ester, M., Kriegel, H.P., Sander, J., Wimmer, M., Xu, X.: Incremental clustering for mining in a data warehousing environment. In: A. Gupta, O. Shmueli, J. Widom (eds.) VLDB’98, Proceedings of 24rd International Conference on Very Large Data Bases, August 24-27, 1998, New York City, New York, USA, pp. 323–333. Morgan Kaufmann (1998)Google Scholar
  3. 3.
    Falkowski, T.: Community Analysis in Dynamic Social Networks. Sierke Verlag, Gttingen (2009)Google Scholar
  4. 4.
    Falkowski, T., Barth, A.: Density-based temporal graph clustering for subgroup detection in social networks. Presented at Conference on Applications of Social Network Analysis (2007)Google Scholar
  5. 5.
    Falkowski, T., Barth, A., Spiliopoulou, M.: Dengraph: A density-based community detection algorithm. In: Proc. of the 2007 IEEE / WIC / ACM International Conference on Web Intelligence, pp. 112–115. IEEE Computer Society, Washington, DC, USA (2007)Google Scholar
  6. 6.
    Falkowski, T., Barth, A., Spiliopoulou, M.: Studying community dynamics with an incremental graph mining algorithm. In: Proc. of the 14 th Americas Conference on Information Systems (AMCIS 2008). Toronto, Canada (2008)Google Scholar
  7. 7.
    Schlitter, N., Falkowski, T.: Mining the dynamics of music preferences from a social networking site. In: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, pp. 243–248. IEEE Computer Society, Washington, DC, USA (2009)Google Scholar
  8. 8.
    Shetty, J., Adibi, J.: Enron email dataset. Tech. rep. (2004). URL

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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