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要旨:
Facial expressions convey both emotional and conversational signals. Research focuses mostly on EMOTIONAL expressions and consistenly finds that these can be reliably distinguished along at least two dimensions: valence and arousal. CONVERSATIONAL expressions, i.e. those conveying mainly communicative meaning, are thought to be less emotional laden. Interestingly, we found evidence pointing towards the same first two underlying dimensions for CONVERSATIONAL expressions when presented dynamically. The question now arises: "Is the emergence of the valence and arousal dimensions for conversational facial expressions based on the emotional content of these expressions?" To answer this, we used questions addressing the emotional (Fontaine et al, 2007) and the conversational content separately. If the distinction of conversational expressions is based on the small amount of emotional information they might contain, we expect emotional content questions to allow a separation of those expressions. Ten native German participants answered a set of 27 questions for 6 emotional and 6 conversational expressions, both presented statically and dynamically, using a rating scale. A dissimilarity matrix was computed for the expressions. To uncover the meaning of the first two underlying dimensions allowing expression differentiation, multidimensional scaling (MDS) was used. Our results show that static and dynamic emotional expressions can only be distinguished by means of emotional content questions. For these emotional expressions, the valence and arousal dimensions emerged in the MDS. In contrast, conversational expressions can be distinguished using conversational content questions but not using emotional content questions. Unlike emotional expressions, dynamic information improved distinction of conversational expressions substantially. We found evidence for valence and arousal to be the underlying dimensions for conversational expressions. Our results suggest that the distinction of conversational expressions along the first two dimensions is based on conversational rather than emotional content. Moreover, different types of facial expressions benefit to different degrees from dynamic information.
