Exploring the similarity space
ACM SIGIR Forum
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Term Weighting Approaches in Automatic Text Retrieval
Term Weighting Approaches in Automatic Text Retrieval
Length Normalization in Degraded Text Collections
Length Normalization in Degraded Text Collections
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
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
Using appraisal groups for sentiment analysis
Proceedings of the 14th ACM international conference on Information and knowledge management
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
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
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
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
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
Introduction to Information Retrieval
Introduction to Information Retrieval
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
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
More than words: syntactic packaging and implicit sentiment
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Joint sentiment/topic model for sentiment analysis
Proceedings of the 18th ACM conference on Information and knowledge management
Improvements that don't add up: ad-hoc retrieval results since 1998
Proceedings of the 18th ACM conference on Information and knowledge management
Text representation using dependency tree subgraphs for sentiment analysis
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Learning word vectors for sentiment analysis
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Aspect ranking: identifying important product aspects from online consumer reviews
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Sentiment classification based on supervised latent n-gram analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
Polarity analysis of texts using discourse structure
Proceedings of the 20th ACM international conference on Information and knowledge management
An information theoretic approach to sentiment polarity classification
Proceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality
Learning lexical subjectivity strength for chinese opinionated sentence identification
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
A study of term weighting schemes using class information for text classification
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Document-level sentiment classification: An empirical comparison between SVM and ANN
Expert Systems with Applications: An International Journal
A comparative study of feature selection and machine learning techniques for sentiment analysis
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Sentiment classification with supervised sequence embedding
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Assembling the optimal sentiment classifiers
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Exploiting emoticons in sentiment analysis
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A boosted SVM based sentiment analysis approach for online opinionated text
Proceedings of the 2013 Research in Adaptive and Convergent Systems
TISA: topic independence scoring algorithm
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
A study of supervised term weighting scheme for sentiment analysis
Expert Systems with Applications: An International Journal
A boosted SVM based ensemble classifier for sentiment analysis of online reviews
ACM SIGAPP Applied Computing Review
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Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated feature weighting schemes from Information Retrieval can enhance classification accuracy. We show that variants of the classic tf.idf scheme adapted to sentiment analysis provide significant increases in accuracy, especially when using a sublinear function for term frequency weights and document frequency smoothing. The techniques are tested on a wide selection of data sets and produce the best accuracy to our knowledge.