Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Emotion classification using massive examples extracted from the web
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
UA-ZBSA: a headline emotion classification through web information
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Annotation of emotions and feelings in texts
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
A text-driven rule-based system for emotion cause detection
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Build Chinese emotion lexicons using a graph-based algorithm and multiple resources
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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Emotion computing is very important for expressive information extraction. In this paper, we provide a robust and versatile emotion annotation scheme based on cognitive emotion theories, which not only can annotate both explicit and implicit emotion expressions, but also can encode different levels of emotion information for the given emotion content. In addition, motivated by a cognitive framework, an automatic emotion annotation system is developed, and large and comparatively high-quality emotion corpora are created for emotion computing, one in Chinese and the other in English. Such an annotation system can be easily adapted for different kinds of emotion applications and be extended to other languages.