Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Extracting semantic orientations of words using spin model
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Emotion classification using massive examples extracted from the web
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Fair news reader: recommending news articles with different sentiments based on user preference
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Improving a method for quantifying readers' impressions of news articles with a regression equation
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Proposal of impression mining from news articles
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Many search systems exist on the Internet. However, no system searches for information based on a query related to a user's sentiment. We propose a system that searches for information based on a user's sentiment. In this paper, we propose a words-of-wisdom search system as a first step of that research. Specifically, we propose a six-dimensional sentiment vector for words-of-wisdom. Next, we propose a method for calculating the value of sentiment words that consist of words-of-wisdom based on our experiment. Subsequently, we calculate sentiment values of words-of-wisdom using the value of sentiment words. We developed a prototype system and conducted experiments.