Detection and application of influence rankings in small group meetings

  • Authors:
  • Rutger Rienks;Dong Zhang;Daniel Gatica-Perez;Wilfried Post

  • Affiliations:
  • University of Twente, Enschede, The Netherlands;IDIAP and EPFL, Martigny, Switzerland;IDIAP and EPFL, Martigny, Switzerland;TNO, Soesterberg, The Netherlands

  • Venue:
  • Proceedings of the 8th international conference on Multimodal interfaces
  • Year:
  • 2006

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Abstract

We address the problem of automatically detecting participant's influence levels in meetings. The impact and social psychological background are discussed. The more influential a participant is, the more he or she influences the outcome of a meeting. Experiments on 40 meetings show that application of statistical (both dynamic and static) models while using simply obtainable features results in a best prediction performance of 70.59% when using a static model, a balanced training set, and three discrete classes: high, normal and low. Application of the detected levels are shown in various ways i.e. in a virtual meeting environment as well as in a meeting browser system.