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
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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With the rapid advance of the Internet, everybody has become able to obtain information from it easily. However. there are no systems which are available to extract and present information suitable to a user's sentiment. We propose a system that searches for information based on a user's sentiment. As described in this this paper, we propose a words-of-wisdom search system as a first step of the research. Specifically, we first propose a multi-dimensional sentiment vector based on Nakamura's proposed 10 categories of sentiments. Next, based on our experiment, we calculate the value of sentiment words included in words-of-wisdom. Subsequently we calculate the sentiment value of words-of-wisdom using a value of sentiment words. We developed a prototype system and conducted experiments.