An Improved Method of Sentiment Analysis of Chinese web Reviews

被引：0
作者：
Yan, Jianzhuo [1 ]
Li, Pengying [1 ]
Fang, Liying [1 ]
机构：
[1] Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China
来源：
2014 SEVENTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID 2014), VOL 1 | 2014年
关键词：
sentiment analysis; opinion mining; aspect extraction; sentiment strength;
D O I：
10.1109/ISCID.2014.237
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The web reviews contain a lot of features of the evaluation object and express the viewpoints or attitudes of the reviewers. Therefore, analyzing them and identifying the sentiment polarity will be significantly important and valuable. This paper uses the appearing-frequency of noun words to extract the aspect words and uses some semantic rules to extract opinion words to form the aspect - opinion word pairs. We use the sentiment orientation-point mutual information (SO-PMI) algorithm to calculate the sentiment strength of opinion words and get the semantic orientation of the opinion words and improved the algorithm. With the Chinese reviews of doctors from the medical websites www.39.net and www.chan120.net, experimental results demonstrate the validity of the proposed method.
引用
收藏
页码：351 / 355
页数：5
相关论文
共 13 条
  • [1] [Anonymous], 2001, P 12 EUR C MACH LEAR, DOI DOI 10.1007/3-540-44795-4_42
  • [2] Hong-We W., 2013, Journal of Management Sciences in China, V16, P64
  • [3] Hu M., 2004, MINING OPINION FEATU
  • [4] Hu M., 2004, P TENTHACM SIGKDD IN, P168
  • [5] Kim S. M., 2006, P WORKSH SENT SUBJ T, P1, DOI DOI 10.3115/1654641.1654642
  • [6] Lu Y, 2010, LECT NOTES COMPUT SC, V6184, P471, DOI 10.1007/978-3-642-14246-8_46
  • [7] Pang B, 2002, P ACL 02 C EMP METH, V10, P79
  • [8] TANG H, 2007, J CHINESE INFORM PRO, V21, P55
  • [9] Turney PD, 2002, 40TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE, P417
  • [10] [姚天昉 YAO Tianfang], 2007, [中文信息学报, Journal of Chinese Information Processing], V21, P73
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