WordNet: a lexical database for English
Communications of the ACM
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Text classification using string kernels
The Journal of Machine Learning Research
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Hierarchical directed acyclic graph kernel: methods for structured natural language data
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Neurocomputing
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
Using measures of semantic relatedness for word sense disambiguation
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Convolution kernels for opinion holder extraction
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A hybrid approach to emotional sentence polarity and intensity classification
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Improving the impact of subjectivity word sense disambiguation on contextual opinion analysis
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Efficient convolution kernels for dependency and constituent syntactic trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
Robust sense-based sentiment classification
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Harnessing WordNet senses for supervised sentiment classification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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Sentiment analysis is an area of research that has gained considerable attention in recent years due to the increasing availability of opinionated information online. The majority of the work in sentiment analysis considers the polarity of word terms rather than the polarity of specific senses of the word but different senses of a word can have different opinion-related properties. In order to address this issue we consider novel semantic features of words in the context of a sentence. We take a sentence as a sequence of words augmented with features based on word sense disambiguation and sentiment lexicons with sense specific opinion-related properties. We then use a factored version of the sequence kernel in a support vector machine, and apply it to sentiment classification of sentences. We evaluate this sentiment analysis methodology on three publicly available corpuses. We also evaluate the effectiveness of several publicly available sense specific polarity lexicons and combinations. Experiments show that our factored approach offers improvements over the surface words baseline and other state-of-the-art kernels.