Community Assessment Using Evidence Networks

  • Folke Mitzlaff
  • Martin Atzmueller
  • Dominik Benz
  • Andreas Hotho
  • Gerd Stumme
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6904)

Abstract

Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups.

This paper proposes an approach for (relative) community assessment. We introduce a set of so-called evidence networks which are capturing typical interactions in social network applications. Thus, we are able to apply a rich set of implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented approach applying user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Folke Mitzlaff
    • 1
  • Martin Atzmueller
    • 1
  • Dominik Benz
    • 1
  • Andreas Hotho
    • 2
  • Gerd Stumme
    • 1
  1. 1.Knowledge and Data Engineering GroupUniversity of KasselKasselGermany
  2. 2.Data Mining and Information Retrieval GroupUniversity of WuerzburgWuerzburgGermany

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