• Article
  • | |
  • Metrics
  • |
  • Reference [88]
  • |
  • Related [20]
  • |
  • Cited by [39]
  • | |
  • Comments
    Abstract:

    This paper surveys the state of the art of sentiment analysis. First, three important tasks of sentiment analysis are summarized and analyzed in detail, including sentiment extraction, sentiment classification, sentiment retrieval and summarization. Then, the evaluation and corpus for sentiment analysis are introduced. Finally, the applications of sentiment analysis are concluded. This paper aims to take a deep insight into the mainstream methods and recent progress in this field, making detailed comparison and analysis.

    Reference
    [1] Hatzivassiloglou V, McKeown KR. Predicting the semantic orientation of adjectives. In: Proc. of the EACL’97. Morristown: ACL, 1997. 174?181.
    [2] Huang XJ, Zhao J. Sentiment analysis for Chinese text. Communications of CCF, 2008,4(2) (in Chinese with English abstract).
    [3] Yao TF, Cheng XW, Xu FY, Uszkoreit H, Wang R. A survey of opinion mining for texts. Journal of Chinese Information Processing, 2008,22(3):71?80 (in Chinese with English abstract).
    [4] Pang B, Lee L. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2008,2(1-2):1?135. [doi: 10.1561/1500000011]
    [5] Zhou LZ, He YK, Wang JY. Survey on research of sentiment analysis. Journal of Computer Applications, 2008,28(11):2725?2728 (in Chinese with English abstract).
    [6] Rao D, Ravichandran D. Semi-Supervised polarity lexicon induction. In: Lascarides A, ed. Proc. of the EACL 2009. Morristown: ACL, 2009. 675?682.
    [7] Wiebe J. Learning subjective adjectives from corpora. In: Schultz AC, ed. Proc. of the AAAI. Menlo Park: AAAI Press, 2000. 735?740.
    [8] Riloff E, Wiebe J. Learning extraction patterns for subjective expressions. In: Collins M, Steedman M, eds. Proc. of the EMNLP 2003. Morristown: ACL, 2003. 105?112.
    [9] Turney P, Littman ML. Measuring praise and criticism: Inference of semantic orientation from association. ACM Trans. on Information Systems, 2003,21(4):315?346. [doi: 10.1145/944012.944013]
    [10] Kim SM, Hovy E. Automatic detection of opinion bearing words and sentences. In: Carbonell JG, Siekmann J, eds. Proc. of the IJCNLP 2005. Morristown: ACL, 2005. 61?66.
    [11] Kim SM, Hovy E. Identifying and analyzing judgment opinions. In: Bilmes J, et al., eds. Proc. of the Joint Human Language Technology/North American Chapter of the ACL Conf. (HLT-NAACL). Morristown: ACL, 2006. 200?207.
    [12] Zhu YL, Min J, Zhou YQ, Huang XJ, Wu LD. Semantic orientation computing based on HowNet. Journal of Chinese Information Processing, 2006,20(1):14?20 (in Chinese with English abstract).
    [13] Andreevskaia A, Bergler S. Mining WordNet for a fuzzy sentiment: Sentiment tag extraction from WordNet glosses. In: McCarthy D, Wintner S, eds. Proc. of the European Chapter of the Association for Computational Linguistics (EACL). Morristown: ACL, 2006. 209?216.
    [14] Su F, Markert K. Subjectivity recognition on word senses via semi-supervised mincuts. In: Ostendorf M, ed. Proc. of the NAACL 2009. Morristown: ACL, 2009. 1?9.
    [15] Esuli A, Sebastiani F. Determining the semantic orientation of terms through gloss analysis. In: Herzog O, ed. Proc. of the ACM SIGIR Conf. on Information and Knowledge Management (CIKM). New York: ACM Press, 2005. 617?624.
    [16] Esuli A, Sebastiani F. Determining term subjectivity and term orientation for opinion mining. In: McCarthy D, Wintner S, eds. Proc. of the European Chapter of the Association for Computational Linguistics (EACL). Morristown: ACL, 2006. 193?200.
    [17] Kamps J, Marx M, Mokken RJ. Using WordNet to measure semantic orientation of adjectives. In: Calzolari N, et al., eds. Proc. of the LREC. 2004. 1115?1118.
    [18] Mihalcea R, Banea C, Wiebe J. Learning multilingual subjective language via cross-lingual projections. In: Carroll J, ed. Proc. of the Association for Computational Linguistics (ACL). Morristown: ACL, 2007. 976?983.
    [19] Wiebe J, Mihalcea R. Word sense and subjectivity. In: Dale R, Paris C, eds. Proc. of the Conf. on Computational Linguistics/Association for Computational Linguistics (COLING/ACL). Morristown: ACL, 2006. 1065?1072.
    [20] Takamura H, Inui T, Okumura M. Extracting semantic orientation of words using spin model. In: Knight K, ed. Proc. of the Association for Computational Linguistics (ACL). Morristown: ACL, 2005. 133?140.
    [21] Yi J, Nasukawa T, Bunescu R. Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques. In: Wu XD, Tuzhilin A, eds. Proc. of the IEEE Int’l Conf. on Data Mining (ICDM). 2003. 427?434.
    [22] Hu M, Liu B. Mining opinion features in customer reviews. In: Hendler JA, ed. Proc. of the AAAI 2004. Menlo Park: AAAI Press, 2004. 755?760.
    [23] Ni MS, Lin HF. Mining product reviews based on association rule and polar analysis. In: Zhu QM, et al., eds. Proc. of the NCIRCS 2007. 2007. 628?634 (in Chinese with English abstract).
    [24] Liu HY, Zhao YY, Qin B, Liu T. Target extraction and sentiment classification. Journal of Chinese Information Processing, 2010, 24(1):84?88 (in Chinese with English abstract).
    [25] Popescu AM, Etzioni O. Extracting product features and opinions from reviews. In: Mooney RJ, ed. Proc. of the HLT/EMNLP 2005. Morristown: ACL, 2005. 339?346.
    [26] Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. Journal of Machine Learning Research, 2003,3:993?1022. [doi: 10.1162/ jmlr.2003.3.4-5.993]
    [27] Blei DM, Ng AY, Jordan MI. Correlated topic models. In: Sch?lkopf B, ed. Advances in NIPS. Hyatt Regency: MIT Press, 2006. 147?154.
    [28] Titov I, McDonald R. Modeling online reviews with multi-grain topic models. In: Huai JP, Chen R, eds. Proc. of the WWW 2008. New York: ACM Press, 2008. 111?120.
    [29] Kim SM, Hovy E. Extracting opinions, opinion holders, and topics expressed in online news media text. In: Dale R, Paris C, eds. Proc. of the ACL Workshop on Sentiment and Subjectivity in Text. 2006. 1?8.
    [30] Stoyanov V, Cardie C. Topic identification for fine-grained opinion analysis. In: McKeown K, ed. Proc. of the Conf. on Computational Linguistics. Morristown: ACL, 2008. 817?824.
    [31] Kim SM, Hovy E. Determining the sentiment of opinions. In: Nirenburg S, ed. Proc. of the Coling 2004. Morristown: ACL, 2004. 1367?1373.
    [32] Choi Y, Cardie C, Riloff E. Identifying sources of opinions with conditional random fields and extraction patterns. In: Mooney RJ, ed. Proc. of the HLT/EMNLP 2005. Morristown: ACL, 2005. 355?362.
    [33] Bethard S, Yu H, Thornton A. Automatic extraction of opinion propositions and their holders. In: Proc. of the AAAI Spring Symp. on Exploring Attitude and Affect in Text. 2004. 22?24.
    [34] Wiebe J, Wilson T, Bell M. Identifying collocations for recognizing opinions. In: Webber BL, ed. Proc. of the ACL/EACL Workshop on Collocation: Computational Extraction, Analysis, and Exploitation. Morristown: ACL, 2001. 24?31.
    [35] Wiebe J, Wilson T. Learning to disambiguate potentially subjective expressions. In: Roth D, van den Bosch A, eds. Proc. of the Conf. on Natural Language Learning (CoNLL). Morristown: ACL, 2002. 112?118.
    [36] Wilson T, Wiebe J, Hwa R. Just how mad are you? Finding strong and weak opinion clauses. In: Hendler JA, ed. Proc. of the AAAI 2004. Menlo Park: AAAI Press, 2004. 761?769.
    [37] Wilson T, Wiebe J, Hwa R. Recognizing strong and weak opinion clauses. Computational Intelligence, 2006,22(2):73?99.
    [38] Whitelaw C, Garg N, Argamon S. Using appraisal groups for sentiment analysis. In: Fuhr N, ed. Proc. of the ACM SIGIR Conf. on Information and Knowledge Management (CIKM). New York: ACM Press, 2005. 625?631.
    [39] Moilanen K, Pulman S. Sentiment composition. In: Mitkov R, ed. Proc. of the Recent Advances in Natural Language Processing Int’l Conf. (RANLP 2007). 2007. 378?382.
    [40] Choi Y, Cardie C. Learning with compositional semantics as structural inference for subsentential sentiment analysis. In: Lapata M, Ng HT, eds. Proc. of the EMNLP 2008. Morristown: ACL, 2008. 793?801.
    [41] Kobayashi N, Inui K, Matsumoto Y. Collecting evaluative expressions for opinion extraction. In: Nagao M, ed. Proc. of the Int’l Joint Conf. on Natural Language Processing (IJCNLP). Morristown: ACL, 2004. 584?589.
    [42] Bloom K, Garg N, Argamon S. Extracting appraisal expressions. In: Sidner C, ed. Proc. of the HLT-NAACL 2007. Morristown: ACL, 2007. 308?315.
    [43] Yao TF, Nie QY, Li JC, Li LL, Lou DC, Chen K, Fu Y. An opinion mining system for Chinese automobile reviews. In: Cao YQ, et al., eds. Proc. of the Frontiers of Chinese Information Processing. Beijing: Tsinghua University Press, 2006. 260?281 (in Chinese with English abstract).
    [44] Xu LH, Lin HF, Zhao J. Construction and analysis of emotional corpus. Journal of Chinese Information Processing, 2008,22(1): 116?122 (in Chinese with English abstract).
    [45] Riloff E, Wiebe J, Phillips W. Exploiting subjectivity classification to improve information extraction. In: Yanco H, ed. Proc. of the AAAI 2005. Menlo Park: AAAI Press, 2005. 1106?1111.
    [46] Hatzivassiloglou V, Wiebe J. Effects of adjective orientation and gradability on sentence subjectivity. In: Kay M, ed. Proc. of the Int’l Conf. on Computational Linguistics (COLING). Morristown: ACL, 2000. 299?305.
    [47] Yu H, Hatzivassiloglou V. Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. In: Collins M, Steedman M, eds. Proc. of the EMNLP 2003. Morristown: ACL, 2003. 129?136.
    [48] Yao TF, Peng SW. A study of the classification approach for Chinese subjective and objective texts. In: Zhu QM, et al., eds. Proc. of the NCIRCS 2007. 2007. 117?123 (in Chinese with English abstract).
    [49] Pang B, Lee L. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In: Scott D, ed. Proc. of the ACL 2004. Morristown: ACL, 2004. 271?278.
    [50] Hu MQ, Liu B. Mining and summarizing customer reviews. In: Kohavi R, ed. Proc. of the KDD 2004. New York: ACM Press, 2004. 168?177.
    [51] Turney P. Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Isabelle P, ed. Proc. of the ACL 2002. Morristown: ACL, 2002. 417?424.
    [52] Pang B, Lee L, Vaithyanathan S. Thumbs up? Sentiment classification using machine learning techniques. In: Isabelle P, ed. Proc. of the EMNLP 2002. Morristown: ACL, 2002. 79?86.
    [53] Cui H, Mittal VO, Datar M. Comparative experiments on sentiment classification for online product reviews. In: Gil Y, Mooney RJ, eds. Proc. of the AAAI 2006. Menlo Park: AAAI Press, 2006. 1265?1270.
    [54] Kim SM, Hovy E. Automatic identification of pro and con reasons in online reviews. In: Dale R, Paris C, eds. Proc. of the COLING/ACL 2006. Morristown: ACL, 2006. 483?490.
    [55] Zhao J, Liu K, Wang G. Adding redundant features for CRFs-based sentence sentiment classification. In: Lapata M, Ng HT, eds. Proc. of the Conf. on Empirical Methods in Natural Language Processing (EMNLP 2008). Morristown: ACL, 2008. 117?126.
    [56] Pang B, Lee L. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In: Knight K, ed. Proc. of the Association for Computational Linguistics (ACL). Morristown: ACL, 2005. 115?124.
    [57] Goldberg AB, Zhu X. Seeing stars when there aren’t many stars: Graph-Based semi-supervised learning for sentiment categorization. In: Bilmes J, et al., eds. Proc. of the HLT-NAACL 2006 Workshop on Textgraphs: Graph-Based Algorithms for Natural Language Processing. Morristown: ACL, 2006. 45?52.
    [58] Lin WH, Wilson T, Wiebe J. Which side are you on? Identifying perspectives at the document and sentence levels. In: Bilmes J, et al., eds. Proc. of the Conf. on Natural Language Learning (CoNLL). Morristown: ACL, 2006. 109?116.
    [59] Kim SM, Hovy E. Crystal: Analyzing predictive opinions on the Web. In: Eisner J, ed. Proc. of the Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Morristown: ACL, 2007. 1056?1064.
    [60] Hurst M, Nigam K. Retrieving topical sentiments from online document collections. In: Proc. of the Document Recognition and Retrieval XI. 2004. 27?34.
    [61] Ounis I, Rijke MD, Macdonald C, Mishne G, Soboroff I. Overview of the TREC-2006 Blog track. In: Proc. of the TREC. 2006.
    [62] Zhang W, Yu C, Meng WY. Opinion retrieval from Blogs. In: Laender A, et al., eds. Proc. of the CIKM. New York: ACM Press, 2007. 831?840.
    [63] Zhang W, Yu C. UIC at TREC 2007 Blog track. In: Proc. of the 16th TREC. 2007.
    [64] Zhang M, Ye XY. A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval. In: Chua TS, Leong MK, eds. Proc. of the ACM Special Interest Group on Information Retrieval (SIGIR). New York: ACM Press, 2008. 411?418.
    [65] Liu B, Hu MQ, Cheng J. Opinion observer: Analyzing and comparing opinions on the Web. In: Ellis A, ed. Proc. of the WWW 2005. New York: ACM Press, 2005. 342?351.
    [66] Carenini G, Ng R, Pauls A. Multi-Document summarization of evaluative text. In: McCarthy D, Wintner S, eds. Proc. of the European Chapter of the Association for Computational Linguistics (EACL). Morristown: ACL, 2006. 305?312.
    [67] Qin B, Zhao YY, Gao LL, Liu T. Recommended or not? Give advice on online products. In: Ma J, et al., eds. Proc. of the 5th Int’l Conf. on Fuzzy Systems and Knowledge Discovery. IEEE Computer Society Press, 2008. 208?212.
    [68] Titov I, McDonald R. A joint model of text and aspect ratings for sentiment summarization. In: McKeown K, ed. Proc. of the ACL 2008. Morristown: ACL, 2008. 308?316.
    [69] Branavan S, Chen H, Eisenstein J. Learning document-level semantic properties from free-text annotations. In: McKeown K, ed. Proc. of the ACL 08: HLT. Morristown: ACL, 2008. 263?271.
    [70] Ku LW, Liang YT, Chen HH. Opinion extraction, summarization and tracking in news and Blog corpora. In: Gil Y, Mooney RJ, eds. Proc. of the AAAI 2006 Spring Symp. on Computational Approaches to Analyzing Weblogs. Menlo Park: AAAI Press, 2006.
    [71] Ounis I, Rijke MD, Macdonald C. Overview of the TREC-2006 Blog track. In: Proc. of the 15th Text Retrieval Conf. (TREC). 2006.
    [72] Zhao J, Xu HB, Huang XJ, Tan SB, Liu K, Zhang Q. Overview of Chinese opinion analysis evaluation 2008. 2008 (in Chinese with English abstract). http://nlpr-web.ia.ac.cn/2008papers/gnhy/nh10.pdf
    [73] Jindal N, Liu B. Identifying comparative sentences in text documents. In: Efthimiadis EN, ed. Proc. of the ACM Special Interest Group on Information Retrieval (SIGIR). New York: ACM Press, 2006. 244?251.
    [74] Wiebe J, Wilson T, Cardie C. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 2005,39(2-3):164?210.
    [75] Ku LW, Lo YS, Chen HH. Using polarity scores of words for sentence-level opinion extraction. In: Proc. of the NTCIR-6 Workshop Meeting. 2007. 316?322.
    [76] Wilson T, Hoffmann P, Somasundaran S. Opinionfinder: A system for subjectivity analysis. In: Mooney RJ, ed. Proc. of the HLT/EMNLP 2005 Demonstration Abstracts. Morristown: ACL, 2005. 34?35.
    [77] Devitt A, Ahmad K. Sentiment polarity identification in financial news: A cohesionbased approach. In: Carroll J, ed. Proc. of the Association for Computational Linguistics (ACL). Morristown: ACL, 2007. 984?991.
    [78] Lita LV, Schlaikjer AH, Hong W. Qualitative dimensions in question answering: Extending the definitional QA task. In: Yanco H, ed. Proc. of the AAAI. Menlo Park: AAAI Press, 2005. 1616?1617.
    附中文参考文献: [2] 黄萱菁,赵军.中文文本情感分析.中国计算机学会通讯,2008,4(2).
    [3] 姚天昉,程希文,徐飞玉,汉思?乌思克尔特,王睿.文本意见挖掘综述.中文信息学报,2008,22(3):71?80.
    [5] 周立柱,贺宇凯,王建勇.情感分析研究综述.计算机应用,2008,28(11):2725?2728.
    [12] 朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算.中文信息学报,2006,20(1):14?20.
    [23] 倪茂树,林鸿飞.基于关联规则和极性分析的商品评论挖掘.见:第3届全国信息检索与内容安全学术会议论文集.2007. 628?634.
    [24] 刘鸿宇,赵妍妍,秦兵,刘挺.评价对象抽取及其倾向性分析.中文信息学报,2010,24(1):84?88.
    [43] 姚天昉,聂青阳,李建超,李林琳,娄德成,陈珂,付宇.一个用于汉语汽车评论的意见挖掘系统.中文信息处理前沿进展——中国中文信息学会成立二十五周年学术年会论文集.2006.260?281.
    [44] 徐琳宏,林鸿飞,赵晶.情感语料库的构建和分析.中文信息学报,2008,22(1):116?122.
    [48] 姚天昉,彭思崴.汉语主客观文本分类方法的研究.见:第3届全国信息检索与内容安全学术会议论文集.2007.117?123.
    [72] 赵军,许洪波,黄萱菁,谭松波,刘康,张奇.中文倾向性分析评测技术报告.2008.
    Comments
    Comments
    分享到微博
    Submit
Get Citation

赵妍妍,秦 兵,刘 挺.文本情感分析.软件学报,2010,21(8):1834-1848

Copy
Share
Article Metrics
  • Abstract:21411
  • PDF: 60647
  • HTML: 0
  • Cited by: 0
History
  • Received:August 14,2009
  • Revised:March 11,2010
You are the first2035312Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063