The Strength of Weak Learnability
Machine Learning
Machine Learning
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
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on 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
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
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
OpinionFinder: a system for subjectivity analysis
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Learning from labeled features using generalized expectation criteria
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Document-Word Co-regularization for Semi-supervised Sentiment Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
A survey on sentiment detection of reviews
Expert Systems with Applications: An International Journal
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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
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Sentiment analysis aims to identify the orientation (positive or negative) of opinions or emotions expressed in documents. Opinion lexicons comprise opinion words expressing prior positive or negative sentiments. In most previous work documents are represented as bags of words and sentiment analysis has been cast a classification problem, where opinion lexicons are only used to enhance the classification models. In this paper we aim to establish the direct connection between document sentiment and opinion words in the documents. We propose two holistic approaches that consider the probability distribution of both opinion words and their polarity for analyzing document sentiment. Our extensive experiments on blogs of 12 topics show that our holistic models significantly improve baseline models using words and their polarity information separately, and is also superior to an existing approach combining both types of information.