Issue No. 04 - Fourth Quarter (2012 vol. 3)
Bruno Lepri , Massachussetts Institute of Technology, Cambridge and Fondazione Bruno Kessler, Trento
Ramanathan Subramanian , University of Trento, Trento
Kyriaki Kalimeri , University of Trento, Trento
Jacopo Staiano , University of Trento, Trento
Fabio Pianesi , Fondazione Bruno Kessler, Trento
Nicu Sebe , University of Trento, Trento
This work investigates the suitability of medium-grained meeting behaviors, namely, speaking time and social attention, for automatic classification of the Extraversion personality trait. Experimental results confirm that these behaviors are indeed effective for the automatic detection of Extraversion. The main findings of our study are that: 1) Speaking time and (some forms of) social gaze are effective indicators of Extraversion, 2) classification accuracy is affected by the amount of time for which meeting behavior is observed, 3) independently considering only the attention received by the target from peers is insufficient, and 4) distribution of social attention of peers plays a crucial role.
Feature extraction, Speech recognition, Ethics, Context awareness, Computer vision, Psychology, Man machine systems, Human factors, Information processing, psychology, User/machine systems, human-information processing, vision and scene understanding
J. Staiano, K. Kalimeri, R. Subramanian, B. Lepri, F. Pianesi and N. Sebe, "Connecting Meeting Behavior with Extraversion—A Systematic Study," in IEEE Transactions on Affective Computing, vol. 3, no. , pp. 443-455, 2012.