基于语义分析的中文微博情感分类方法

doi:10.6040/j.issn.1671-9352.3.2014.069

山东大学学报（理学版） ›› 2014, Vol. 49 ›› Issue (11): 14-21.doi: 10.6040/j.issn.1671-9352.3.2014.069

基于语义分析的中文微博情感分类方法

杨佳能^1,3, 阳爱民², 周咏梅²

1. 广东外语外贸大学国际工商管理学院, 广东广州 510006;
2. 广东外语外贸大学思科信息学院, 广东广州 510006;
3. 广东省电信规划设计院有限公司, 广东广州 510630

收稿日期:2014-08-28 修回日期:2014-10-24 出版日期:2014-11-20 发布日期:2014-11-25
通讯作者: 阳爱民(1970- ),男,教授,博士,研究方向为计算语言学、文本情感分析.E-mail: amyang18@163.com E-mail:amyang18@163.com
作者简介:杨佳能(1987- ),男,硕士研究生,研究方向为机器学习、文本情感分析.E-mail: tizzi@163.com
基金资助:
国家社科基金资助项目(12BYY045);教育部新世纪优秀人才支持计划资助项目(NCET-12-0939); 广东省教育厅科技创新项目(2013KJCX0067)

Sentiment classification method of Chinese Micro-blog based on semantic analysis

YANG Jia-neng^1,3, YANG Ai-min², ZHOU Yong-mei²

1. School of Management, Guangdong University of Foreign Studies, Guangzhou 510006, Guangdong, China;
2. Cisco School of Informatics, Guangdong University of Foreign Studies, Guangzhou 510006, Guangdong, China;
3. Guangdong Planning and Designing Institute of Telecommunications Co., Ltd., Guangzhou 510630, Guangdong, China

Received:2014-08-28 Revised:2014-10-24 Online:2014-11-20 Published:2014-11-25

摘要/Abstract

摘要： 通过分析微博的结构特点,提出了一种基于语义分析的中文微博情感分类方法.首先构建了表情符号情感词典和网络用语情感词典;然后结合词典资源对微博文本进行依存句法分析并且构建情感表达式树;最后根据制定的规则计算微博文本的情感强度,依据强度值判断微博的情感倾向类别.实验结果验证了该方法的有效性,也表明所构建的表情符号情感词典和网络用语情感词典能够有效增强情感分类器的性能.

关键词: 网络用语, 情感分析, 表情符号, 依存句法分析, 中文微博

Abstract: By analyzing the structural features of Chinese Micro-blog, a sentiment classification method based on semantic analysis was proposed. For the proposed method, firstly, an emoticons sentiment lexicon and a network language sentiment lexicon were built. Then by using these two lexicons and the dependency parsing results, the sentiment expression Binary Tree was constructed. Finally, the sentiment strength, which was calculated by the established rules, was applied into the sentiment classification. Experimental results show that this method is effective and two built sentiment lexicons can better enhance the performance of the sentiment analysis system.

Key words: sentiment analysis, network language, Chinese Micro-blog, dependency parsing, emoticons

中图分类号:

TP391

杨佳能, 阳爱民, 周咏梅. 基于语义分析的中文微博情感分类方法[J]. 山东大学学报（理学版）, 2014, 49(11): 14-21.

YANG Jia-neng, YANG Ai-min, ZHOU Yong-mei. Sentiment classification method of Chinese Micro-blog based on semantic analysis[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(11): 14-21.

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基于语义分析的中文微博情感分类方法

Sentiment classification method of Chinese Micro-blog based on semantic analysis

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