Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Learning Subjective Adjectives from Corpora
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Mining product reputations on the Web
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Robustness of regularized linear classification methods in text categorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
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 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
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Sentiment Mining in WebFountain
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Using cocitation information to estimate political orientation in web documents
Knowledge and Information Systems
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for 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
Emotions from text: machine learning for text-based emotion prediction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Active Learning with Feedback on Features and Instances
The Journal of Machine Learning Research
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
Expert Systems with Applications: An International Journal
A survey on sentiment detection of reviews
Expert Systems with Applications: An International Journal
Which side are you on?: identifying perspectives at the document and sentence levels
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
The impact of time on the accuracy of sentiment classifiers created from a web log corpus
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Domain-specific sentiment analysis using contextual feature generation
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Sentiment classification of online Cantonese reviews by supervised machine learning approaches
International Journal of Web Engineering and Technology
WebKDD'06 Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
Sentiment classification of Chinese traveler reviews by support vector machine algorithm
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Cross-Domain Contextualization of Sentiment Lexicons
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Expert Systems with Applications: An International Journal
Bootstrapping polarity classifiers with rule-based classification
Language Resources and Evaluation
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Sentiment classification is the task of labeling a review document according to the polarity of its prevailing opinion (favorable or unfavorable). In approaching this problem, a model builder often has three sources of information available: a small collection of labeled documents, a large collection of unlabeled documents, and human understanding of language. Ideally, a learning method will utilize all three sources. To accomplish this goal, we generalize an existing procedure that uses the latter two.We extend this procedure by re-interpreting it as a Naive Bayes model for document sentiment. Viewed as such, it can also be seen to extract a pair of derived features that are linearly combined to predict sentiment. This perspective allows us to improve upon previous methods, primarily through two strategies: incorporating additional derived features into the model and, where possible, using labeled data to estimate their relative influence.