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Detection and application of influence rankings in small group meetings

Author: Rienks, R. · Zhang, D. · Gatica-Perez, D. · Post, W.
Institution: TNO Defensie en Veiligheid
Source:ICMI'06 : 8th International Conference on Multimodal Interfaces, Conference Proceeding, 257-264
Identifier: 239643
doi: doi:10.1145/1180995.1181047
ISBN: 159593541X ; 9781595935410
Keywords: Psychology · Dominance detection · Influence detection · Machine learning · Small group research · Learning systems · Mathematical models · Static analysis · Dominance detection · Influence detection · Small group research · Behavioral research


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. Copyright 2006 ACM.