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New Technology of Library and Information Service  2016, Vol. 32 Issue (2): 67-74    DOI: 10.11925/infotech.1003-3513.2016.02.09
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Building Sentiment Analysis Dictionary for Chinese Book Reviews
Guo Shunli(),Zhang Xiangxian
School of Management, Jilin University, Changchun 130022, China
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Abstract  

[Objective] This study aims to build a sentiment analysis dictionary for the Chinese book reviews. [Methods] We first divided the user’s sentiments into seven categories, which were used to create the Chinese book review emotional word list. Then, chose seed terms from that list with the help of a basic sentiment analysis lexicon. Finally, used the improved SO-PMI algorithm and synonym expansion method to classify target terms from the real book reviews. [Results] With the help of this new book review sentiment analysis dictionary, the average precision, recall and F1 rates were 0.90, 0.83 and 0.85 respectively. [Limitations] The test corpus is relatively small, which might influence our results. [Conclusions] The proposed method was an effective and reliable way to conduct sentiment analysis for the Chinese book reviews.
Key words： Chinese book reviews      Sentiment analysis dictionary      Seed word      Sentiment classification      SO-PMI     
Received: 11 September 2015      Published: 08 March 2016
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Guo Shunli
Zhang Xiangxian

Cite this article:

Guo Shunli,Zhang Xiangxian. Building Sentiment Analysis Dictionary for Chinese Book Reviews. New Technology of Library and Information Service, 2016, 32(2): 67-74.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2016.02.09     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2016/V32/I2/67

[1] 图书评论[EB/OL]. [2015-03-03]. .
[1] (Book Reviews [EB/OL]. [2015-03-03].
[2] Andreevskaia A, Bergler S.Mining WordNet for a Fuzzy Sentiment: Sentiment Tag Extraction from WordNet Glosses [C]. In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics. 2006: 209-216.
[3] Turney P D.Thumbs up or Thumbs down?: Semantic Orientation Applied to Unsupervised Classification of Reviews [C]. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. 2002: 417-424.
[4] Subasic P, Huettner A.Affect Analysis of Text Using Fuzzy Semantic Typing [C]. In: Proceedings of the 9th IEEE International Conference on Fuzzy Systems. IEEE, 2001.
[5] 柳位平, 朱艳辉, 栗春亮, 等. 中文基础情感词词典构建方法研究[J]. 计算机应用, 2009, 29(10): 2875-2877.
[5] (Liu Weiping, Zhu Yanhui, Li Chunliang, et al.Research on Building Chinese Basic Semantic Lexicon[J]. Journal of Computer Application, 2009, 29(10): 2875-2877.)
[6] 李钰. 微博情感词典的构建及其在微博情感分析中的应用研究[D]. 郑州: 郑州大学, 2014.
[6] (Li Yu.Microblog Emotional Dictionary Built and Application on Sentiment Analysis of Microblog [D]. Zhengzhou: Zhengzhou University, 2014.)
[7] 桂斌, 杨小平, 张中夏, 等. 基于微博表情符号的情感词典构建研究[J]. 北京理工大学学报, 2014, 34(5):537-541.
[7] (Gui Bin, Yang Xiaoping, Zhang Zhongxia, et al.Research on Building Lexicon for Sentiment Analysis Based on the Chinese Microblogging Smiley[J]. Transactions of Beijing Institute of Technology, 2014, 34(5): 537-541.)
[8] 周咏梅, 阳爱民, 杨佳能. 一种新闻评论情感词典的构建方法[J]. 计算机科学, 2014, 41(8):67-69, 80.
[8] (Zhou Yongmei, Yang Aimin, Yang Jianeng.Construction Method of Sentiment Lexicon for New Reviews[J]. Computer Science, 2014, 41(8): 67-69, 80.)
[9] 蒋盛益, 阳垚, 廖静欣. 中文音乐情感词典构建及情感分类方法研究[J]. 计算机工程与应用, 2014, 50(24):118-121, 163.
[9] (Jiang Shengyi, Yang Yao, Liao Jingxin.Research of Building Chinese Musical Emotional Lexicon and Emotional Classification[J]. Computer Engineering and Applications, 2014, 50(24): 118-121, 163.)
[10] Yang A M, Lin J H, Zhou Y M, et al. Research on Building a Chinese Sentiment Lexicon Based on SO-PMI [J]. Applied Mechanics and Materials, 2013, 263-266: 1688-1693.
[11] 余珍芝. 中文网络产品评论的情感分析关键技术研究[D]. 杭州: 杭州电子科技大学, 2011.
[11] (Yu Zhenzhi.Research on the Key Technologies of Chinese Online Product Review’s Sentiment Analysis [D]. Hangzhou: Hangzhou Dianzi University, 2011.)
[12] 李明. 面向微博电影评论的情感分类研究[D]. 昆明: 云南财经大学, 2014.
[12] (Li Ming.Emotion Classification for Weibo Movie Reviews [D]. Kunming: Yunnan Finance University, 2014.)
[13] 徐琳宏, 林鸿飞, 潘宇, 等. 情感词汇本体的构造[J]. 情报学报, 2008, 27(2):180-185.
[13] (Xu Linhong, Lin Hongfei, Pan Yu, et al.Constructing the Affective Lexicon Ontology[J]. Journal of the China Society for Scientific and Technical Information, 2008, 27(2): 180-185.
[14] 武汉大学ROST虚拟学习团队. ROST CM6 [EB/OL]. [2015-03-05]. .
[14] (Virtual Learning Team of Wuhan University. ROST CM6 [EB/OL]. [2015-03-05].
[15] HIT-CIR Tongyici Cilin (Extended) [EB/OL]. [2015-03-05]. .
[16] 知网. 《知网》情感分析用词语集: Beta [EB/OL]. [2015-03-03]. .
[16] (HowNet. HowNet Sentiment Analysis Using Word Set: Beta [EB/OL]. [2015-03-03].
[17] 中文情感极性词典NTUSD [EB/OL]. [2015-03-08]. .
[17] (Chinese Emotion Words Dictionary (NTUS) [EB/OL]. [2015-03-08].
[18] 集搜客GooSeeker网络爬虫[EB/OL]. [2015-09-05]. .
[18] (Ji Souke GooSeeker Web Spiders [EB/OL]. [2015-09-05].
[19] 朱嫣岚, 闵锦, 周雅倩, 等. 基于HowNet的词汇语义倾向性计算[J]. 中文信息学报, 2006, 20(1): 14-20.
[19] (Zhu Yanlan, Min Jin, Zhou Yaqian, et al.Semantic Orientation Computing Based on HowNet[J]. Journal of Chinese Information Processing, 2006, 20(1): 14-20.)
[20] 杜锐. 面向中文微博文本的情感分类研究[D]. 长沙: 湖南工业大学, 2014.
[20] (Du Rui.Rearch on Sentiment Classification for Chinese Microblog Text [D]. Changsha: Hunan University of Technology, 2014.)
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