Measuring the Topical Specificity of Online Communities

  • Matthew Rowe
  • Claudia Wagner
  • Markus Strohmaier
  • Harith Alani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7882)

Abstract

For community managers and hosts it is not only important to identify the current key topics of a community but also to assess the specificity level of the community for: a) creating sub-communities, and: b) anticipating community behaviour and topical evolution. In this paper we present an approach that empirically characterises the topical specificity of online community forums by measuring the abstraction of semantic concepts discussed within such forums. We present a range of concept abstraction measures that function over concept graphs - i.e. resource type-hierarchies and SKOS category structures - and demonstrate the efficacy of our method with an empirical evaluation using a ground truth ranking of forums. Our results show that the proposed approach outperforms a random baseline and that resource type-hierarchies work well when predicting the topical specificity of any forum with various abstraction measures.

Keywords

Online Community Composite Function Type Graph Eigenvector Centrality Concept Graph 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Matthew Rowe
    • 1
  • Claudia Wagner
    • 2
  • Markus Strohmaier
    • 3
  • Harith Alani
    • 4
  1. 1.School of Computing and CommunicationsLancaster UniversityLancasterUK
  2. 2.Institute for Information and Communication TechnologiesJOANNEUM RESEARCHGrazAustria
  3. 3.Knowledge Management Institute and Know-CenterGraz University of TechnologyGrazAustria
  4. 4.Knowledge Media InstituteThe Open UniversityMilton KeynesUK

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