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Lepri B.,FBK Foundation Bruno Kessler | Subramanian R.,University of Trento | Kalimeri K.,University of Trento | Staiano J.,University of Trento | And 2 more authors.
IEEE Transactions on Affective Computing | Year: 2012

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. © 2010-2012 IEEE.

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