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News Sentiment Classification for Chinese Document Based on Semantic Orientation
SHI Zhenliang *
School of Software Engineering of BUPT, Beijing University of Posts and Telecommunications
*Correspondence author
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Funding: none
Opened online: 9 May 2011
Accepted by: none
Citation: SHI Zhenliang.News Sentiment Classification for Chinese Document Based on Semantic Orientation[OL]. [ 9 May 2011] http://en.paper.edu.cn/en_releasepaper/content/4423193
 
 
Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. In this paper, we focus on the news sentiment classification based on Chinese document-level. On the systematically analyzing the importance and difficulties of the news sentiment classification, this paper proposes an improved sentiment classification approach for Chinese document based on semantic orientation. The approach has four steps: (1) the news documents are pre-processed; (2) the sentiment words and the negative words are integrated processed; (3) the topic words and the sentiment words are integrated processed; (4) the weight is calculated based on a sentiment word dictionary and the context information. The experimental results show that our improved method can achieve better performance in Chinese document level sentiment classification.
Keywords:Document Sentiment Classification; Opinion Mining; Semantic Orientation; Syntactic Path
 
 
 

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