JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (11): 67-73.doi: 10.6040/j.issn.1671-9352.0.2015.082

Previous Articles     Next Articles

Product reviews sentiment classification in Micro-blog based on cascaded conditional random field

HE Yan-xiang1,2, LIU Jian-bo1,2, SUN Song-tao1,2, WEN Wei-dong1,2   

  1. 1. Computer School of Wuhan University, Wuhan 430072, Hubei, China;
    2. State Key Laboratory of Software Engineering, Wuhan 430072, Hubei, China
  • Received:2015-02-12 Revised:2015-11-11 Online:2015-11-20 Published:2015-12-09

Abstract: Product reviews are subjective comments submitted by customers. Nowadays, product reviews are in the form of Micro-blog text which is typically very short but with varied structures. We proposed a novel sentiment classification method for product reviews from Micro-blog based on cascaded Conditional Random Field(CRF). First, review sentences were divided into a number of clauses based on the theory of clausal pivot. Then, features of the Chinese clause sequences were exploited to train a coarse-grained CRF sentiment classification model. Meanwhile, features of the Chinese character sequences within clauses were exploited to train a fine-grained CRF sentiment classification model. The experimental evaluation shows that the proposed method is better than the state-of-the-art ones.

Key words: Micro-blog, sentiment analysis, theory of clausal pivot, CRF

CLC Number: 

  • TP391
[1] NASUKAWA T, YI J. Sentiment analysis:capturing favorability using natural language processing[C]//Proceedings of the 2nd international conference on Knowledge capture. New York:ACM, 2003:70-77.
[2] DAVE K, LAWRENCE S, PENNOCK D M. Mining the peanut gallery:opinion extraction and semantic classification of product reviews[C]//Proceedings of the 12th International Conference on World Wide Web, 2003:519-528.
[3] 邢福义. 小句中枢说[J]. 中国语文, 1995, 6:420-428.
[4] PANG B, LEE L. Opinion mining and sentiment analysis[J]. Foundations and Trends in Information Retrieval, 2008, 2(1-2):1-135.
[5] 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 Bin, LIU Ting. Sentiment analysis[J]. Journal of Software, 2010, 21(8):1834-1848.
[6] LIU B. Sentiment analysis and opinion mining[J]. Synthesis Lectures on Human Language Technologies, 2012, 5(1):1-167.
[7] HU Minqing, LIU Bing. Mining and summarizing customer reviews[C]//Proceedings of KDD '04.New York:ACM, 2004:168-177.
[8] HU Minqing, LIU Bing. Opinion extraction and summarization on the web[C]//Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-06).Menlo Park:AAAI Press, 2006, 7:1621-1624.
[9] YU H, HATZIVASSILOGLOU V. Towards answering opinion questions:separating facts from opinions and identifying the polarity of opinion sentences[C]//Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing. Philadelphia:Association for Computational Linguistics, 2003:129-136.
[10] SHEN Y, LI S, ZHENG L, et al. Emotion mining research on Micro-blog[C]//Proceedings of the 1st IEEE Symposium on Web Society. Piscataway:IEEE, 2009:71-75.
[11] 谢丽星,周明,孙茂松. 基于层次结构的多策略中文微博情感分析和特征抽取[J]. 中文信息学报, 2012, 26(1):73-83. XIE Lixing, ZHOU Ming, SUN Maosong.Hierarchical structure based hybrid approach to sentiment analysis of Chinese Micro-blog and its feature extraction[J]. Journal of Chinese Information Processing, 2012, 26(1):73-83.
[12] CHOI Y, CARDIE C, RILOFF E, et al. Identifying sources of opinions with conditional random fields and extraction patterns[C]//Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Philadelphia:Association for Computational Linguistics, 2005:355-362.
[13] MAO Y, LEBANON G. Isotonic conditional random fields and local sentiment flow[C]//Proceedings of the Neural Information Processing Systems. 2007:961-968.
[14] PANG B, LEE L, Vaithyanathan S. Thumbs up:sentiment classification using machine learning techniques[C]//Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing.Somerset:Association for Computational Linguistics, 2002:79-86.
[15] MCDONALD R, HANNAN K, NEYLON T, et al. Structured models for fine-to-coarse sentiment analysis[C]//Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Philadelphia:Association for Computational Linguistics, 2007, 45(1):432-439.
[16] SADAMITSU K, SEKINE S, YAMAMOTO M. Sentiment analysis based on probabilistic models using inter-sentence information[C]//Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC'08). Luxembourg:European Language Resources Association,2008:2892-2896.
[17] TCKSTRM O, MCDONALD R. Discovering fine-grained sentiment with latent variable structured prediction models[C]//Proceedings of the 33rd European Conference on Information Retrieval.Heidelberg:Springer-Verlag Berlin, 2011:368-374.
[18] TCKSTRM O, MCDONALD R. Semi-supervised latent variable models for sentence-level sentiment analysis[C]//Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics:Human Language Technologies. Philadelphia:Association for Computational Linguistics, 2011:569-574.
[19] FANG L, HUANG M, ZHU X. Exploring weakly supervised latent sentiment explanations for aspect-level review analysis[C]//Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management. New York:ACM, 2013:1057-1066.
[20] CHOI Y, BRECK E, CARDIE C. Joint extraction of entities and relations for opinion recognition[C]//Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. Philadelphia:Association for Computational Linguistics, 2006:431-439.
[21] 王根, 赵军. 基于多重冗余标记 CRF 的句子情感分析研究[J]. 中文信息学报, 2007, 21(5):51-55. WANG Gen, ZHAO Jun. Sentence sentiment analysis based on multi-redundant-labeled CRFs[J]. Journal of Chinese Information Processing, 2007, 21(5):51-55.
[22] 刘康,赵军. 基于层叠 CRF 模型的句子褒贬度分析研究[J]. 中文信息学报, 2008, 22(1):123-128. LIU Kang, ZHAO Jun. Sentence sentiment analysis based on cascaded CRFs model[J]. Journal of Chinese Information Processing, 2008, 22(1):123-128.
[23] 王荣洋,鞠久鹏,李寿山. 基于 CRF 的评价对象抽取特征研究[J]. 中文信息学报, 2012, 26(2):56-61. WANG Rongyang, JU Jiupeng, LI Shoushan. Extraction of opinion targets based on shallow parsing features[J]. Journal of Chinese Information Processing, 2012, 26(2):56-61.
[24] 郑敏洁,雷志城,廖祥文. 基于层叠 CRF 的中文句子评价对象抽取[J]. 中文信息学报, 2013, 27(3):69-76. ZHENG Minjie, LEI Zhicheng, LIAO Xiangwen. Indentify sentiment-objects from Chinese sententence based on cascaded conditional random fields[J].Journal of Chinese Information Processing, 2013, 27(3):69-76.
[25] 何炎祥,罗楚威,胡彬尧. 基于CRF和规则相结合的地理命名实体识别方法[J]. 计算机应用与软件,2015,32(1):179-185. HE Yanxiang, LUO Chuwei, HU Binyao. Geographic entity recognition method based on CRF model and rules combination[J]. Computer Applications and Software, 2015, 32(1):179-185.
[26] 乌达巴拉,汪增福. 一种扩展式CRFs的短语情感倾向性分析方法研究[J]. 中文信息学报,2015,29(1):155-162. ODBAL, WANG Zengfu. Phrase-level sentiment analysis approach based on yet another CRFs[J]. Journal of Chinese Information Processing, 2015, 29(1):155-162.
[27] 栗伟,赵大哲,李博. CRF与规则相结合的医学病历实体识别[J]. 计算机应用研究,2015,4:1082-1086. LI Wei, ZHAO Dazhe, LI Bo, et al. Combining CRF and rule based medical named entity recognition[J]. Application Research of Computers, 2015, 4:1082-1086.
[28] 黄忠廉. 小句中枢全译说[J]. 汉语学报, 2005(2):62-69.
[1] YU Chuan-ming, FENG Bo-lin, TIAN Xin, AN Lu. Deep representative learning based sentiment analysis in the cross-lingual environment [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 13-23.
[2] CHEN Xin, XUE Yun, LU Xin, LI Wan-li, ZHAO Hong-ya, HU Xiao-hui. Text feature extraction method for sentiment analysis based on order-preserving submatrix and frequent sequential pattern mining [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(3): 36-45.
[3] ZHANG Zhong-jun, ZHANG Wen-juan, YU Lai-hang, LI Run-chuan. A community division method based on network distance and content similarity in micro-blog social network [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(7): 97-103.
[4] HU Mo-zhi, YAO Tian-fang. Recognition of Chinese Micro-blog sentiment polarity and extraction of opinion target [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2016, 51(7): 81-89.
[5] SUN He, LI Shu-qin, L(¨overU)Xue-qiang, LIU Ke-hui. Recognition of geographical entity in city complaints of Micro-blog [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2016, 51(3): 77-85.
[6] WANG Li-ren, YU Zheng-tao, WANG Yan-bing, GAO Sheng-xiang, LI Xian-hui. Micro-blogging topic mining based on supervised LDA user interest model [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(09): 36-41.
[7] ZAN Hong-ying, WU Yong-gang, JIA Yu-xiang, NIU Gui-ling. Chinese Micro-blog named entity linking based on multisource knowledge [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(07): 9-16.
[8] ZHU Zhu, LI Shou-shan, DAI Min, ZHOU Guo-dong. Opinion target extraction with active-learning and automatic annotation [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(07): 38-44.
[9] TANG Bo, CHEN Guang, WANG Xing-ya, WANG Fei, CHEN Xiao-hui. Analysis on new word detection and sentiment orientation in Micro-blog [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(01): 20-25.
[10] ZHOU Wen, ZHANG Shu-qing, OUYANG Chun-ping, LIU Zhi-ming, YANG Xiao-hua. Topic sentiment analysis of Chinese news based on emotional dependency tuple [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(12): 1-6.
[11] 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.
[12] ZHU Xi, DONG Xi-shuang, GUAN Yi, LIU Zhi-guang. Sentiment analysis of Chinese Micro-blog based on semi-supervised learning [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(11): 37-42.
[13] LIU Ming, ZAN Hong-ying, YUAN Hui-bin. Key sentiment sentence prediction using SVM and RNN [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(11): 68-73.
[14] SUN Song-tao, HE Yan-xiang, CAI Rui, LI Fei, HE Fei-yan. Comparative study of methods for Micro-blog sentiment evaluation tasks [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(11): 43-50.
[15] LIU Pei-yu, ZHANG Yan-hui, ZHU Zhen-fang, XUN Jing. Micro-blog orientation analysis based on emotion symbol [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(11): 8-13.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!