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http://dx.doi.org/10.14695/KJSOS.2015.18.1.103

The Construction of a Domain-Specific Sentiment Dictionary Using Graph-based Semi-supervised Learning Method  

Kim, Jung-Ho (Department of Computer Engineering, Korea Aerospace University)
Oh, Yean-Ju (Department of Computer Engineering, Korea Aerospace University)
Chae, Soo-Hoan (The School of Electronics and Telecommunication, Korea Aerospace University)
Publication Information
Science of Emotion and Sensibility / v.18, no.1, 2015 , pp. 103-110 More about this Journal
Abstract
Sentiment lexicon is an essential element for expressing sentiment on a text or recognizing sentiment from a text. We propose a graph-based semi-supervised learning method to construct a sentiment dictionary as sentiment lexicon set. In particular, we focus on the construction of domain-specific sentiment dictionary. The proposed method makes up a graph according to lexicons and proximity among lexicons, and sentiments of some lexicons which already know their sentiment values are propagated throughout all of the lexicons on the graph. There are two typical types of the sentiment lexicon, sentiment words and sentiment phrase, and we construct a sentiment dictionary by creating each graph of them and infer sentiment of all sentiment lexicons. In order to verify our proposed method, we constructed a sentiment dictionary specific to the movie domain, and conducted sentiment classification experiments with it. As a result, it have been shown that the classification performance using the sentiment dictionary is better than the other using typical general-purpose sentiment dictionary.
Keywords
sentiment lexicon; sentiment dictionary; sentiment classification; sentiment word; sentiment phrase; graph; semi-supervised learning;
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