Affective computing
Multimodal human-computer interaction: A survey
Computer Vision and Image Understanding
International Journal of Artificial Intelligence in Education
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards affective camera control in games
User Modeling and User-Adapted Interaction
Affective Computing: From Laughter to IEEE
IEEE Transactions on Affective Computing
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
IEEE Transactions on Affective Computing
AutoTutor: an intelligent tutoring system with mixed-initiative dialogue
IEEE Transactions on Education
Monitoring affect states during effortful problem solving activities
International Journal of Artificial Intelligence in Education
Opinion Bias Detection with Social Preference Learning in Social Data
International Journal on Semantic Web & Information Systems
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One of the primary goals of Affective Computing (AC) is to develop computer interfaces that automatically detect and respond to users' emotions. Despite significant progress, "basic emotions" (e.g., anger, disgust, sadness) have been emphasized in AC at the expense of other non-basic emotions. The present paper questions this emphasis by analyzing data from five studies that systematically tracked both basic and non-basic emotions. The results indicate that engagement, boredom, confusion, and frustration (all non-basic emotions) occurred at five times the rate of basic emotions after generalizing across tasks, interfaces, and methodologies. Implications of these findings for AC are discussed