Conversation analysis at work: detection of conflict in competitive discussions through semi-automatic turn-organization analysis

Pesarin, A., Cristani, M., Murino, V. and Vinciarelli, A. (2012) Conversation analysis at work: detection of conflict in competitive discussions through semi-automatic turn-organization analysis. Cognitive Processing, 13(S2), pp. 533-540. (doi: 10.1007/s10339-011-0417-9)

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Publisher's URL: http://dx.doi.org/10.1007/s10339-011-0417-9

Abstract

This study proposes a semi-automatic approach aimed at detecting conflict in conversations. The approach is based on statistical techniques capable of identifying turn-organization regularities associated with conflict. The only manual step of the process is the segmentation of the conversations into turns (time intervals during which only one person talks) and overlapping speech segments (time intervals during which several persons talk at the same time). The rest of the process takes place automatically and the results show that conflictual exchanges can be detected with Precision and Recall around 70% (the experiments have been performed over 6 h of political debates). The approach brings two main benefits: the first is the possibility of analyzing potentially large amounts of conversational data with a limited effort, the second is that the model parameters provide indications on what turn-regularities are most likely to account for the presence of conflict.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vinciarelli, Professor Alessandro
Authors: Pesarin, A., Cristani, M., Murino, V., and Vinciarelli, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Cognitive Processing
ISSN:1612-4782
ISSN (Online):1612-4790
Published Online:19 October 2011

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