The grammar of sense: Using part-of-speech tags as a first step in semantic disambiguation
Natural Language Engineering
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
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Computational Linguistics
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on 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
Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
Management Science
Contextual phrase-level polarity analysis using lexical affect scoring and syntactic N-grams
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
RBEM: a rule based approach to polarity detection
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
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We propose a new rule-based system for phrase-level polarity analysis and show how it benefits from empirically validating its polarity composition through surveys with human subjects. The system's twolayer architecture and its underlying structure, i.e. its composition model, are presented. Two functions for polarity aggregation are introduced that operate on newly defined semantic categories. These categories detach a word's syntactic from its semantic behavior. An experimental setup is described that we use to carry out a thorough evaluation. It incorporates a newly created German-language data set that is made freely and publicly available. This data set contains polarity annotations at word-level, phrase-level and sentence-level and facilitates comparability between different studies and reproducibility of our results.