JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2014, Vol. 44 ›› Issue (6): 15-18.doi: 10.6040/j.issn.1672-3961.1.2014.108

Previous Articles     Next Articles

The sentiment mining method based on extended sentiment dictionary and integrated features

XU Xiaodan, DUAN Zhengjie, CHEN Zhongyu   

  1. Mathematics, Physics and Information Engineering College, Zhejiang Normal University, Jinhua 321004, Zhejiang, China
  • Received:2014-05-12 Revised:2014-10-28 Online:2014-12-20 Published:2014-05-12

Abstract: In the traditional classification method, only one feature was considered, that was not good enough for the precision. In order to improve the precision, a classification method based on integrated features was provided. First, the emotional tendency value of one word was calculated according to an extended sentiment dictionary; then after the CHI selection, the weights of the positive and negative emotion word posterior probability in the Bayesian model were adjusted acrodding to its tendency value. In the experiments, four kinds of corpus such as hotel and movie reviews were used, compared with other three methods, the integrated features method was better. The results showed the precision of classification was improved and the dimension of the feature was reduced.

Key words: orientation analysis, sentiment lexicon, sentiment mining, feature-selection, classificaiton

CLC Number: 

  • TP391
[1] PANG Bo, LEE Lillian. Opinion mining and sentiment analysis[J]. Foundations and Trends in Information Retrieval, 2008, 2(1-2):11-35.
[2] LIN Weihao, WILSON Theresa, WIEBE Janyce. Identifying perspectives at the document and sentence levels[C]//Proceeding of the Conference on Natural Language Learning (CoNLL). Morristown:ACL Press, 2006:109-116.
[3] KIM Soomin, HOVY Eduard. Crystal: Analyzing predictive opinions on the Web[C]//Proceeding of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Morristown: ACL Press, 2007:1056-1064.
[4] 赵妍妍,秦兵,刘挺.文本情感分析[J].软件学报,2010,21(8):1834-1848. ZHAO Yanyan, QIN Bing, LIU Ting. Sentiment analysis[J]. Journal of Software, 2010, 21(8):1834-1848.
[5] 吴琼,谭松波,程学旗.中文情感倾向性分析的相关研究进展[J].信息技术快报,2010,8:16-31. WU qiong, TAN Songbo, CHENG Xueqi.The progress in the study of chinese text orientation analysis[J]. Information Technology Letter, 2010, 8:16-31.
[6] HU Mingqing, LIU Bing. Mining and summarizing customer reviews[C]//Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York: ACM Press, 2004:168-177.
[7] PANG Bo, LEE Lillian, VAITHYANATHAN Shivakumar.Sentiment classification using machine learning techniques[C]//Proceeding of Empirical Methods in Natural Language Processing.Morristown:ACL Press, 2002:79-86.
[8] YU Hong, HATZIVASSILOGLOU Vasileios.Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences[C]//Proceedings of the EMNLP 2003. Morristown: ACL Press, 2003:129-136.
[9] RAO Delip, RAVICHANDRAN Deepak. Semi-Supervised polarity lexicon induction[C]//Proceedings of the EACL 2009. Morristown:ACL Press, 2009:675-682.
[10] TAKAMURA Hiroya, INUI Takashi, OKUMURA Manabu. Extracting semantic orientation of words using spin model[C]//Proceedings of the Association for Computational Linguistics. Morristown: ACL Press, 2005:133-140.
[11] LIU Qun, LI Sujian. Word similarity computing based on howNet[C]//Proceedings of the 3th Chinese Lexical Semantic Workshop. Taibei:CLSW Press, 2002:45-56. [12] 江敏,肖诗斌,王弘蔚,等.一种改进的基于《知网》的词语语义相似度计算[J].中文信息学报, 2008, 22(5):84-89. JIANG Min, XIAO Shibin, WANG Hongwei, et al. An improved word similarity computing method based on hownet[J].Journal of Chinese Information Processing, 2008, 22(5):84-89.
[13] 朱嫣岚,闵锦,周雅倩,等.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20. ZHU Yanlan, MIN Jin, ZHOU Yaqian, et al.Sementic orientation computing based on howNet[J]. Journal of Chinese Information Processing, 2006, 20(1):14-20.
[14] TURNEY Peter. Semantic orientation applied to unsupervised classification of reviews[C]//Proceedings of ACL. Morristown:ACL Press, 2002:417-424.
[15] 杨超,冯时,王大玲,等.基于情感扩展技术的网络舆情倾向性分析[J].小型微型计算机系统,2010,04: 691-695. YANG Chao, FENG Shi, WANG Daling, et al. Analysis on Web public opinion orientation on extending sentiment lexicon[J].Journal of Chinese Computer System, 2010, 04: 691-695.
[16] KU Lunwei, LO Yongsheng, CHEN Hsinhsi. Using opinion scores ofwords for sentence-level opinion extraction[C]//Proceedings of the 6th NACSIS Test Collections for IR Workshop Meeting on Evaluation of Information Access Technologies.Tokyo:NTCIR Press, 2007:316-322.
[17] YANG Yiming, PEDERSEN Jan. A comparative study on feature selection in text categorization[C]//Proceeding of the 14th International Conference on Machine Learning.San Francisco: Morgan Kaufmann Press, 1997: 412-420.
[1] LIN Jianghao, ZHOU Yongmei, YANG Aimin, CHEN Jin. Building of domain sentiment lexicon based on word2vec [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 40-47.
[2] ZHOU Yongmei1, YANG Aimin1, LIN Jianghao2. A method of building Chinese microblog sentiment lexicon [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(3): 36-40.
Full text



No Suggested Reading articles found!