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Nonverbal Social Sensing in Action: Unobtrusive Recording and Extracting of Nonverbal Behavior in Social Interactions Illustrated with a Research Example

Frauendorfer, Denise ; Schmid Mast, Marianne ; Nguyen, Laurent ; Gatica-Perez, Daniel

In: Journal of Nonverbal Behavior, 2014, vol. 38, no. 2, p. 231-245

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    Titre
    • Nonverbal Social Sensing in Action: Unobtrusive Recording and Extracting of Nonverbal Behavior in Social Interactions Illustrated with a Research Example
    Auteur
    • Frauendorfer, Denise. Department of Work and Organizational Psychology, University of Neuchatel, Emile-Argand 11, 2000, Neuchatel, Switzerland
    • Schmid Mast, Marianne. Department of Work and Organizational Psychology, University of Neuchatel, Emile-Argand 11, 2000, Neuchatel, Switzerland
    • Nguyen, Laurent. Idiap Research Institute, Ecole Polytechnique Federal de Lausanne (EPFL), Lausanne, Switzerland
    • Gatica-Perez, Daniel. Idiap Research Institute, Ecole Polytechnique Federal de Lausanne (EPFL), Lausanne, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Journal of Nonverbal Behavior, 2014, vol. 38, no. 2, p. 231-245. Springer US; http://www.springer-ny.com
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:326306
    Summary
    Nonverbal behavior coding is typically conducted by "hand”. To remedy this time and resource intensive undertaking, we illustrate how nonverbal social sensing, defined as the automated recording and extracting of nonverbal behavior via ubiquitous social sensing platforms, can be achieved. More precisely, we show how and what kind of nonverbal cues can be extracted and to what extent automated extracted nonverbal cues can be validly obtained with an illustrative research example. In a job interview, the applicant's vocal and visual nonverbal immediacy behavior was automatically sensed and extracted. Results show that the applicant's nonverbal behavior can be validly extracted. Moreover, both visual and vocal applicant nonverbal behavior predict recruiter hiring decision, which is in line with previous findings on manually coded applicant nonverbal behavior. Finally, applicant average turn duration, tempo variation, and gazing best predict recruiter hiring decision. Results and implications of such a nonverbal social sensing for future research are discussed.