A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
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?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
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-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
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
Using emoticons to reduce dependency in machine learning techniques for sentiment classification
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Towards well-grounded phrase-level polarity analysis
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
SentiCorr: Multilingual Sentiment Analysis of Personal Correspondence
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
Twitter, MySpace, Digg: Unsupervised Sentiment Analysis in Social Media
ACM Transactions on Intelligent Systems and Technology (TIST)
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
Cross-lingual polarity detection with machine translation
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
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We propose the Rule-Based Emission Model (RBEM) algorithm for polarity detection. RBEM uses several kinds of heuristic rules to create an emissive model on polarity patterns. We extensively experiment with our approach on English and Dutch messages extracted from Twitter. Thus we also illustrate that RBEM can be used in multilingual settings and is applicable to social media characterized by use of not always regular language constructs. We demonstrate that designing such an algorithm instead of applying the state-of-the art general purpose classification techniques is a reasonable choice for the automated sentiment classification in practice. Using RBEM we can design a competitive multilingual sentiment classification system showing promising accuracy results of 78.8% on the considered datasets. We provide some further evidence that RBEM-based systems are easy to debug, improve over time and adapt to new application domains.