Word association norms, mutual information, and lexicography
Computational Linguistics
A model of textual affect sensing using real-world knowledge
Proceedings of the 8th international conference on Intelligent user interfaces
Syntactic-Based Methods for Measuring Word Similarity
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
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
Emotion Sensitive News Agent: An Approach Towards User Centric Emotion Sensing from the News
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Learning to identify emotions in text
Proceedings of the 2008 ACM symposium on Applied computing
UA-ZBSA: a headline emotion classification through web information
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UPAR7: a knowledge-based system for headline sentiment tagging
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Sentence level sentiment analysis in the presence of conjuncts using linguistic analysis
ECIR'07 Proceedings of the 29th European conference on IR research
Evaluation of unsupervised emotion models to textual affect recognition
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Hierarchical versus flat classification of emotions in text
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Recognition of affect, judgment, and appreciation in text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
An exploration of features for recognizing word emotion
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Using Web-Intelligence for Excavating the Emerging Meaning of Target-Concepts
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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Emotion detection from text is a relatively new classification task. This paper proposes a novel unsupervised context-based approach to detecting emotion from text at the sentence level. The proposed methodology does not depend on any existing manually crafted affect lexicons such as Word Net-Affect, thereby rendering our model flexible enough to classify sentences beyond Ekman's model of six basic emotions. Our method computes an emotion vector for each potential affect bearing word based on the semantic relatedness between words and various emotion concepts. The scores are then fine tuned using the syntactic dependencies within the sentence structure. Extensive evaluation on various data sets shows that our framework is a more generic and practical solution to the emotion classification problem and yields significantly more accurate results than recent unsupervised approaches.