The syntactic process
A model of textual affect sensing using real-world knowledge
Proceedings of the 8th international conference on Intelligent user interfaces
Predicting student emotions in computer-human tutoring dialogues
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Real-Life emotion representation and detection in call centers data
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
DocEmoX: A System for the Typography-Derived Emotional Annotation of Documents
UAHCI '09 Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services
Modeling reader's emotional state response on document's typographic elements
Advances in Human-Computer Interaction
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For a robot to make effective and friendly interaction with human users, it is important to keep track of emotional changes in utterance properly. Emotions have traditionally been characterized by intuitive but atomic categories or as points in evaluation-activity dimensions. However, this characterization falls short of capturing subtle emotional changes either in narration or in text, where the vast majority of information is presented with a host of linguistic constructions that convey emotional information. We propose a novel representation scheme for emotions, so that such important features as duration, target and intensity can also be treated as first-class citizens and systematically accounted for. We argue that it is with this new mode of representation that the subtlety of the emotional flow in utterance can be properly addressed. We use this representation to encode the emotional states and intentions of characters in the drama scripts for soap opera and describe how it is utilized in conjunction with parsing for lexicalized grammars.