Gaining Insight in Social Networks with Biclustering and Triclustering

  • Dmitry Gnatyshak
  • Dmitry I. Ignatov
  • Alexander Semenov
  • Jonas Poelmans
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 128)


We combine bi- and triclustering to analyse data collected from the Russian online social network Vkontakte. Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users’ interests as tags and use them to describe Vkontakte groups. After this social tagging process we can recommend to a particular user relevant groups to join or new friends from interesting groups which have a similar taste. We present some preliminary results and explain how we are going to apply these methods on massive data repositories.


Formal Concept Analysis Biclustering and Triclustering Online Social Networks Web 2.0 and Social Computing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dmitry Gnatyshak
    • 1
  • Dmitry I. Ignatov
    • 1
  • Alexander Semenov
    • 1
  • Jonas Poelmans
    • 1
    • 2
  1. 1.Higher School of EconomicsNational Research UniversityRussia
  2. 2.Katholieke Universiteit LeuvenBelgium

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