Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on 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
Summarization system evaluation revisited: N-gram graphs
ACM Transactions on Speech and Language Processing (TSLP)
Joint extraction of entities and relations for opinion recognition
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Exploration of Affect Sensing from Speech and Metaphorical Text
Edutainment '09 Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development
NAACL-Demonstrations '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Demonstration Session
SemEval-2007 task 14: affective text
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
CLaC and CLaC-NB: knowledge-based and corpus-based approaches to sentiment tagging
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
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Intuition dictates that figurative language and especially metaphorical expressions should convey sentiment. It is the aim of this work to validate this intuition by showing that figurative language (metaphors) appearing in a sentence drive the polarity of that sentence. Towards this target, the current article proposes an approach for sentiment analysis of sentences where figurative language plays a dominant role. This approach applies Word Sense Disambiguation aiming to assign polarity to word senses rather than tokens. Sentence polarity is determined using the individual polarities for metaphorical senses as well as other contextual information. Experimental evaluation shows that the proposed method achieves high scores in comparison with other state-of-the-art approaches tested on the same corpora. Finally, experimental results provide supportive evidence that this method is also well suited for corpora consisting of literal and figurative language sentences.