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Analysis of Group Conversations: Modeling Social Verticality

  • Oya Aran
  • Daniel Gatica-Perez

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.

Keywords

Latent Dirichlet Allocation Visual Activity Influence Model Microphone Array Prosodic Feature 
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.

Notes

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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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Idiap Research InstituteMartignySwitzerland

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