Making large-scale support vector machine learning practical
Advances in kernel methods
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
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
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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
The sentimental factor: improving review classification via human-provided information
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Assessing Sentiment of Text by Semantic Dependency and Contextual Valence Analysis
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Sentiment analysis of blogs by combining lexical knowledge with text classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Semi-supervised polarity lexicon induction
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Learning with compositional semantics as structural inference for subsentential sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
SELC: a self-supervised model for sentiment classification
Proceedings of the 18th ACM conference on Information and knowledge management
The effect of negation on sentiment analysis and retrieval effectiveness
Proceedings of the 18th ACM conference on Information and knowledge management
Mine the easy, classify the hard: a semi-supervised approach to automatic sentiment classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Subjectivity word sense disambiguation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
The viability of web-derived polarity lexicons
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Last but definitely not least: on the role of the last sentence in automatic polarity-classification
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
A survey on the role of negation in sentiment analysis
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
Lexicon-based methods for sentiment analysis
Computational Linguistics
Domain adaptation by constraining inter-domain variability of latent feature representation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Improving the impact of subjectivity word sense disambiguation on contextual opinion analysis
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Creating subjective and objective sentence classifiers from unannotated texts
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Harnessing WordNet senses for supervised sentiment classification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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In this article, we examine the effectiveness of bootstrapping supervised machine-learning polarity classifiers with the help of a domain-independent rule-based classifier that relies on a lexical resource, i.e., a polarity lexicon and a set of linguistic rules. The benefit of this method is that though no labeled training data are required, it allows a classifier to capture in-domain knowledge by training a supervised classifier with in-domain features, such as bag of words, on instances labeled by a rule-based classifier. Thus, this approach can be considered as a simple and effective method for domain adaptation. Among the list of components of this approach, we investigate how important the quality of the rule-based classifier is and what features are useful for the supervised classifier. In particular, the former addresses the issue in how far linguistic modeling is relevant for this task. We not only examine how this method performs under more difficult settings in which classes are not balanced and mixed reviews are included in the data set but also compare how this linguistically-driven method relates to state-of-the-art statistical domain adaptation.