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New Technology of Library and Information Service  2014, Vol. 30 Issue (5): 74-82    DOI: 10.11925/infotech.1003-3513.2014.05.10
INFORMATION ANALYSIS AND RESEARCH Current Issue | Archive | Adv Search |
Research on Construction of Feature-Sentiment Ontology and Sentiment Analysis
Du Jiazhong1, Xu Jian1, Liu Ying2
1 School of Information Management, Sun Yat-Sen University, Guangzhou 510006, China;
2 Sun Yat-Sen University Libraries, Guangzhou 510275, China
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[Objective] In a specific domain, sentiment analysis, mostly based on general lexicon, cannot identify the context-specific sentiment belonging to the domain. Also, the same word in the specific domain shows different polarities (positive, negative, neutral) when describing different properties. The objective of this paper is to solve the problems described above. [Methods] A sentiment analysis approach based on domain-oriented specific sentiment phrases is proposed. By developing feature-sentiment Ontology, general sentiment and specific sentiment can be divided during the process of sentiment analysis. [Results] The proposed method shows fairly better results of precision and recall in terms of phrase-level sentiment analysis. [Limitations] In order to get better analysis, the Ontology should cover the concepts in the related field as much as possible and should be well-built; the authors ignore the syntactic rules during the concept extraction and sentiment analysis, because the product comments are not normative; in the phase of sentiment analysis, the authors assume that the context like conjunction would not affect the polarity. [Conclusions] The new method not only makes improvement on sentiment analysis by solving the problem described above, but also proposes a new way for sentiment lexicon management.

Key wordsSentiment analysis      Domain sentiment phrase      Ontology      Online review     
Received: 31 December 2013      Published: 06 June 2014
:  G250  

Cite this article:

Du Jiazhong, Xu Jian, Liu Ying. Research on Construction of Feature-Sentiment Ontology and Sentiment Analysis. New Technology of Library and Information Service, 2014, 30(5): 74-82.

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