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Computer Analysis of Human Behavior pp 293–322Cite as

Analysis of Group Conversations: Modeling Social Verticality

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Abstract

This chapter presents computational methods for the analysis of social interaction. We focus on nonverbal behavior of social interaction, in particular social verticality, such as dominance, leadership, and roles. We describe processing, feature extraction, and inference methods that are widely used in the computational social interaction analysis literature. In the last section of the chapter, we present four case studies on dominance estimation, identifying emergent leadership, role recognition, and analysis of leadership styles.

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Acknowledgements

This work is supported by the EU FP7 Marie Curie Intra-European Fellowship project “Automatic Analysis of Group Conversations via Visual Cues in nonverbal Communication” (NOVICOM), and by the Swiss National Science Foundation under the National Centre of Competence in Research (NCCR) on “Interactive Multimodal Information Management” (IM2) and by the Sinergia project on “Sensing and Analysing Organizational Nonverbal Behaviour” (SONVB). The authors would like to thank Dinesh Jayagopi, Dairazalia Sanchez-Cortes, and Gokul Chittaranjan for their contributions to several studies presented in this chapter.

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Authors and Affiliations

  1. Idiap Research Institute, Martigny, Switzerland

    Oya Aran & Daniel Gatica-Perez

Authors
  1. Oya Aran
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  2. Daniel Gatica-Perez
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Correspondence to Oya Aran .

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Editors and Affiliations

  1. Department of Computer Engineering, Boğaziçi University, Bebek, 34342, Istanbul, Turkey

    Albert Ali Salah

  2. Informatics Institute, University of Amsterdam, Science Park 904, Amsterdam, 1098 XH, Netherlands

    Theo Gevers

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Aran, O., Gatica-Perez, D. (2011). Analysis of Group Conversations: Modeling Social Verticality. In: Salah, A., Gevers, T. (eds) Computer Analysis of Human Behavior. Springer, London. https://doi.org/10.1007/978-0-85729-994-9_11

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  • DOI: https://doi.org/10.1007/978-0-85729-994-9_11

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-993-2

  • Online ISBN: 978-0-85729-994-9

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