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Dominance Detection in Meetings Using Easily Obtainable Features

  • Rutger Rienks
  • Dirk Heylen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3869)

Abstract

We show that, using a Support Vector Machine classifier, it is possible to determine with a 75% success rate who dominated a particular meeting on the basis of a few basic features. We discuss the corpus we have used, the way we had people judge dominance and the features that were used.

Keywords

Goal Orientation Dominance Ranking Meeting Participant Dominance Level Neural Information Processing System 
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 2006

Authors and Affiliations

  • Rutger Rienks
    • 1
  • Dirk Heylen
    • 1
  1. 1.Human Media Interaction (HMI)University of TwenteEnschedeThe Netherlands

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