Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
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
Extracting Opinions Relating to Consumer Electronic Goods from Web Pages
Proceedings of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering
Collecting evaluative expressions for opinion extraction
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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This paper proposes the method of building dictionaries for extracting reputation information. We propose a method of building a highly credible dictionary from the staggering volume of information that customers post on Web pages. The principle of our proposed method is based on assigning a certainty factor which represents the probability that extracted words really do express a feature or evaluation expression and registering only words which have a certainty factor greater than a pre-set threshold value. As a result of experiment, the method of building a highly credible dictionary has been established.