AniSAM & AniAvatar – Animated Visualizations of Affective States

Tools that provide visual feedback about emotions to the user in the form of an avatar or an emoticon have become increasingly important. While a great deal of effort has already been put into the reliable and accurate automatic detection of emotions, only very little is known about how this information about affective states should be displayed in a comprehensible way to the user. In the present study, three newly developed feedback tools were evaluated. The tools were developed on the basis of an existing non-verbal questionnaire to represent two dimensions of emotion (i.e. valence and arousal) based on the circumplex model of affect. A total number of 826 participants were tested, using different vignettes that describe situations with specific affective content. Employing three newly developed affective feedback tools (AniSAM, AniAvatar and MergedSAM), the ratings obtained were compared to ratings using the original SAM instrument, a wellestablished questionnaire to measure affect. Results indicated that the animated feedback increased the accuracy of the arousal representation. Furthermore, valence feedback was more accurate when provided with an animated manikin-based tool rather than an avatar-based tool. This provided first evidence for the usufulness of animated tools offering visual feedback on user emotion. All instruments need to undergo further development. AniSAM and AniAvatar can be downloaded for purposes of practical applications and further research.

Published in:
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 4828-4837
Presented at:
CHI Conference on Human Factors in Computing Systems, San José, California, USA, May 7-12, 2016
New York, USA, ACM

 Record created 2017-09-05, last modified 2018-09-13

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