A statistical parsing framework for sentiment classification

Computational Linguistics

Volumn 41, Issue 2, 2015, Pages 265-308

  Dong, Li ^a   Wei, Furu ^b   Liu, Shujie ^b   Zhou, Ming ^b   Xu, Ke ^a  

^a BEIHANG UNIVERSITY   (China)

^b MICROSOFT RESEARCH ASIA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONTEXT FREE GRAMMARS; FORESTRY; FORMAL LANGUAGES; SENTIMENT ANALYSIS;

FORMAL DESCRIPTION; POLARITY MODELS; SENTENCE LEVEL; SENTIMENT CLASSIFICATION; STATISTICAL PARSER; STATISTICAL PARSING; SYNTACTIC ANNOTATION; SYNTACTIC PARSING;

SYNTACTICS;

EID: 84931065275     PISSN: 08912017     EISSN: 15309312     Source Type: Journal    
DOI: 10.1162/COLI_a_00221     Document Type: Article

References (86)

1. Agarwal, Apoorv, Boyi Xie, Ilia Vovsha, Owen Rambow, and Rebecca Passonneau. 2011. Sentiment analysis of twitter data. In Proceedings of the Workshop on Languages in Social Media, LSM '11, pages 30-38, Stroudsburg, PA.
2. Agrawal, Rakesh and Ramakrishnan Srikant. 1994. Fast algorithms for mining association rules in large databases. In Proceedings of the 20th International Conference on Very Large Data Bases, VLDB '94, pages 487-499, San Francisco, CA.
3. Artzi, Yoav and Luke Zettlemoyer. 2013. Weakly supervised learning of semantic parsers for mapping instructions to actions. Transactions of the Association for Computational Linguistics, 1(1): 49-62.
4. Bao, Junwei, Nan Duan, Ming Zhou, and Tiejun Zhao. 2014. Knowledge-based question answering as machine translation. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 967-976, Baltimore, MD.
5. Charniak, Eugene. 1997. Statistical parsing with a context-free grammar and word statistics. In Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Conference on Innovative Applications of Artificial Intelligence, AAAI'97/IAAI'97, pages 598-603, Providence, RI.
6. Charniak, Eugene and Mark Johnson. 2005. Coarse-to-fine n-best parsing and maxent discriminative reranking. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, ACL '05, pages 173-180, Stroudsburg, PA.
7. Chiang, David. 2007. Hierarchical phrase-based translation. Computational Linguistics, 33(2): 201-228.
8. Choi, Yejin and Claire Cardie. 2008. Learning with compositional semantics as structural inference for subsentential sentiment analysis. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '08, pages 793-801, Stroudsburg, PA.
9. Choi, Yejin and Claire Cardie. 2009a. Adapting a polarity lexicon using integer linear programming for domain-specific sentiment classification. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2-Volume 2, EMNLP '09, pages 590-598, Stroudsburg, PA.
10. Choi, Yejin and Claire Cardie. 2009b. Adapting a polarity lexicon using integer linear programming for domain-specific sentiment classification. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2-Volume 2, pages 590-598, Singapore.
11. Choi, Yejin and Claire Cardie. 2010. Hierarchical sequential learning for extracting opinions and their attributes. In Proceedings of the ACL 2010 Conference Short Papers, ACLShort '10, pages 269-274, Stroudsburg, PA.
12. Chomsky, Noam. 1956. Three models for the description of language. IRE Transactions on Information Theory, 2(3): 113-124.
13. Clarke, James, Dan Goldwasser, Ming-Wei Chang, and Dan Roth. 2010. Driving semantic parsing from the world's response. In Proceedings of the Fourteenth Conference on Computational Natural Language Learning, CoNLL '10, pages 18-27, Stroudsburg, PA.
14. Cocke, John. 1969. Programming Languages and Their Compilers: Preliminary Notes. Courant Institute of Mathematical Sciences, New York University.
15. Councill, Isaac G., Ryan McDonald, and Leonid Velikovich. 2010. What's great and what's not: Learning to classify the scope of negation for improved sentiment analysis. In Proceedings of the Workshop on Negation and Speculation in Natural Language Processing, NeSp-NLP '10, pages 51-59, Stroudsburg, PA.
16. Cui, Hang, Vibhu Mittal, and Mayur Datar. 2006. Comparative experiments on sentiment classification for online product reviews. In Proceedings of the 21st National Conference on Artificial Intelligence-Volume 2, AAAI'06, pages 1, 265-1, 270, Boston, MA.
17. Davidov, Dmitry, Oren Tsur, and Ari Rappoport. 2010. Enhanced sentiment learning using twitter hashtags and smileys. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, COLING '10, pages 241-249, Stroudsburg, PA.
18. de Marneffe, Marie-Catherine, Christopher D. Manning, and Christopher Potts. 2010. "was it good? it was provocative. " Learning the meaning of scalar adjectives. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL '10, pages 167-176, Stroudsburg, PA.
19. Dong, Li, Furu Wei, Ming Zhou, and Ke Xu. 2014. Adaptive multi-compositionality for recursive neural models with applications to sentiment analysis. In AAAI Conference on Artificial Intelligence, pages 1, 537-1, 543, Quebec.
20. Duchi, John, Elad Hazan, and Yoram Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. Journal of Machine Learning Research, 12: 2121-2159.
21. Fan, Rong-En, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008. Liblinear: A library for large linear classification. Journal of Machine Learning Research, 9: 1871-1874.
22. Good, Irving John. 1953. The population frequencies of species and the estimation of population parameters. Biometrika, 40(3-4): 237-264.
23. Goodman, Joshua. 1999. Semiring parsing. Computational Linguistics, 25(4): 573-605.
24. Hall, David, Greg Durrett, and Dan Klein. 2014. Less grammar, more features. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 228-237, Baltimore, MD.
25. Hatzivassiloglou, Vasileios and Kathleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics, ACL '98, pages 174-181, Stroudsburg, PA.
26. Jia, Lifeng, Clement Yu, and Weiyi Meng. 2009. The effect of negation on sentiment analysis and retrieval effectiveness. In Conference on Information and Knowledge Management, pages 1, 827-1, 830, Hong Kong.
27. Kaji, Nobuhiro and Masaru Kitsuregawa. 2007. Building lexicon for sentiment analysis from massive collection of HTML documents. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 1, 075-1, 083, Prague.
28. Kamps, Jaap, Robert J. Mokken, Maarten Marx, and Maarten de Rijke. 2004. Using WordNet to measure semantic orientation of adjectives. In Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC 2004), volume IV, pages 1, 115-1, 118, Paris.
29. Kanayama, Hiroshi and Tetsuya Nasukawa. 2006. Fully automatic lexicon expansion for domain-oriented sentiment analysis. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, EMNLP '06, pages 355-363, Stroudsburg, PA.
30. Kasami, Tadao. 1965. An efficient recognition and syntax-analysis algorithm for context-free languages. Technical report AFCRL-65-758, Air Force Cambridge Research Lab, Bedford, MA.
31. Kate, Rohit J. and Raymond J. Mooney. 2006. Using string-kernels for learning semantic parsers. In ACL 2006: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the ACL, pages 913-920, Morristown, NJ.
32. Kennedy, Alistair and Diana Inkpen. 2006. Sentiment classification of movie reviews using contextual valence shifters. Computational Intelligence, 22: 110-125.
33. Klein, Dan and Christopher D. Manning. 2003. Accurate unlexicalized parsing. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics-Volume 1, ACL '03, pages 423-430, Stroudsburg, PA.
34. Klenner, Manfred, Stefanos Petrakis, and Angela Fahrni. 2009. Robust compositional polarity classification. In Proceedings of the International Conference RANLP-2009, pages 180-184, Borovets.
35. Krestel, Ralf and Stefan Siersdorfer. 2013. Generating contextualized sentiment lexica based on latent topics and user ratings. In Proceedings of the 24th ACM Conference on Hypertext and Social Media, HT '13, pages 129-138, New York, NY.
36. Krishnamurthy, Jayant and Tom M. Mitchell. 2012. Weakly supervised training of semantic parsers. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL '12, pages 754-765, Stroudsburg, PA.
37. Kübler, Sandra, Ryan McDonald, and Joakim Nivre. 2009. Dependency parsing. Synthesis Lectures on Human Language Technologies, 1(1): 1-127.
38. Li, Peng, Yang Liu, and Maosong Sun. 2013. An extended ghkm algorithm for inducing Lambda-SCFG. In Conference on Artificial Intelligence, pages 605-611, Bellevue, WA.
39. Liang, Percy, Michael I. Jordan, and Dan Klein. 2013. Learning dependency-based compositional semantics. Computational Linguistics, 39(2): 389-446.
40. Liu, Bing. 2012. Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies. Morgan & Claypool Publishers.
41. Liu, Jingjing and Stephanie Seneff. 2009. Review sentiment scoring via a parse-and-paraphrase paradigm. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1-Volume 1, EMNLP '09, pages 161-169, Stroudsburg, PA.
42. Liu, Shizhu, Gady Agam, and David A. Grossman. 2012. Generalized sentiment-bearing expression features for sentiment analysis. In International Conference on Computational Linguistics, pages 733-744, Mumbai.
43. Lu, Yue, Malú Castellanos, Umeshwar Dayal, and Cheng Xiang Zhai. 2011. Automatic construction of a context-aware sentiment lexicon: an optimization approach. In International World Wide Web Conference, pages 347-356, Hyderabad.
44. Maas, Andrew L., Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011. Learning word vectors for sentiment analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1, HLT '11, pages 142-150, Stroudsburg, PA.
45. Manning, Christopher D., Prabhakar Raghavan, and Hinrich Schütze. 2008. Introduction to Information Retrieval. Cambridge University Press, New York.
46. Marcus, Mitchell P., Mary Ann Marcinkiewicz, and Beatrice Santorini. 1993. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19(2): 313-330.
47. Matsumoto, Shotaro, Hiroya Takamura, and Manabu Okumura. 2005. Sentiment classification using word sub-sequences and dependency sub-trees. In Proceedings of the 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD'05, pages 301-311, Hanoi.
48. McDonald, Ryan, Koby Crammer, and Fernando Pereira. 2005. Online large-margin training of dependency parsers. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL '05, pages 91-98, Stroudsburg, PA.
49. McDonald, Ryan, Kerry Hannan, Tyler Neylon, MikeWells, and Jeff Reynar. 2007. Structured models for fine-to-coarse sentiment analysis. In Proceedings of the Association for Computational Linguistics (ACL), pages 432-439, Prague.
50. Moilanen, Karo and Stephen Pulman. 2007. Sentiment composition. In Proceedings of Recent Advances in Natural Language Processing (RANLP 2007), pages 378-382, Borovets.
51. Moilanen, Karo, Stephen Pulman, and Yue Zhang. 2010. Packed feelings and ordered sentiments: Sentiment parsing with quasi-compositional polarity sequencing and compression. In Proceedings of the 1st Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2010) at the 19th European Conference on Artificial Intelligence (ECAI 2010), pages 36-43, Lisbon.
52. Mudinas, Andrius, Dell Zhang, and Mark Levene. 2012. Combining lexicon and learning based approaches for concept-level sentiment analysis. In Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM '12, pages 5: 1-5: 8, New York, NY.
53. Nakagawa, Tetsuji, Kentaro Inui, and Sadao Kurohashi. 2010. Dependency tree-based sentiment classification using CRFS with hidden variables. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, HLT '10, pages 786-794, Stroudsburg, PA.
54. Pang, Bo and Lillian Lee. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proceedings of the 42nd Meeting of the Association for Computational Linguistics (ACL'04), Main Volume, pages 271-278, Barcelona.
55. Pang, Bo and Lillian Lee. 2005. Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL '05, pages 115-124, Stroudsburg, PA.
56. Pang, Bo and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2): 1-135.
57. Pang, Bo, Lillian Lee, and Shivakumar Vaithyanathan. 2002. Thumbs up?: Sentiment classification using machine learning techniques. In Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing-Volume 10, EMNLP '02, pages 79-86, Stroudsburg, PA.
58. Polanyi, Livia and Annie Zaenen. 2006. Contextual valence shifters. In J. G. Shanahan, Y. Qu, and J. Wiebe, editors, Computing Attitude and Affect in Text: Theory and Applications. Springer Netherlands, pages 1-10.
59. Quirk, R. 1985. A Comprehensive Grammar of the English Language. Longman.
60. Raymond, Ruifang Ge and J. Mooney. 2006. Discriminative reranking for semantic parsing. In Proceedings of the COLING/ACL on Main Conference Poster Sessions, COLING-ACL '06, pages 263-270, Stroudsburg, PA.
61. Robbins, H. and S. Monro. 1951. A stochastic approximation method. Annals of Mathematical Statistics, 22: 400-407.
62. Saurí, Roser. 2008. A Factuality Profiler for Eventualities in Text. Ph. D. thesis, Brandeis University.
63. Shieber, Stuart M., Yves Schabes, and Fernando C. N. Pereira. 1995. Principles and implementation of deductive parsing. Journal of Logic Programming, 24(1-2): 3-36.
64. Socher, Richard, Brody Huval, Christopher D. Manning, and Andrew Y. Ng. 2012. Semantic compositionality through recursive matrix-vector spaces. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL '12, pages 1, 201-1, 211, Stroudsburg, PA.
65. Socher, Richard, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning. 2011. Semi-supervised recursive autoencoders for predicting sentiment distributions. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '11, pages 151-161, Stroudsburg, PA.
66. Socher, Richard, Alex Perelygin, Jean Y. Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1, 631-1, 642, Seattle, WA.
67. Stolcke, Andreas. 2002. SRILM: An extensible language modeling toolkit. In Proceedings of the 7th International Conference on Spoken Language Processing ICSLP 2002, pages 901-904, Denver, CO.
68. Taboada, Maite, Julian Brooke, Milan Tofiloski, Kimberly Voll, and Manfred Stede. 2011. Lexicon-based methods for sentiment analysis. Computational Linguistics, 37(2): 267-307.
69. Täckström, Oscar and Ryan McDonald. 2011a. Discovering fine-grained sentiment with latent variable structured prediction models. In Proceedings of the 33rd European Conference on Advances in Information Retrieval, ECIR'11, pages 368-374, Berlin.
70. Täckström, Oscar and Ryan McDonald. 2011b. Semi-supervised latent variable models for sentence-level sentiment analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers-Volume 2, HLT '11, pages 569-574, Stroudsburg, PA.
71. Takamura, Hiroya, Takashi Inui, and Manabu Okumura. 2005. Extracting semantic orientations of words using spin model. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, ACL '05, pages 133-140, Stroudsburg, PA.
72. Tu, Zhaopeng, Yifan He, Jennifer Foster, Josef van Genabith, Qun Liu, and Shouxun Lin. 2012. Identifying high-impact sub-structures for convolution kernels in document-level sentiment classification. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers-Volume 2, ACL '12, pages 338-343, Stroudsburg, PA.
73. Turney, Peter D. 2002. Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, ACL '02, pages 417-424, Stroudsburg, PA.
74. Velikovich, Leonid, Sasha Blair-Goldensohn, Kerry Hannan, and Ryan McDonald. 2010. The viability ofWeb-derived polarity lexicons. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, HLT '10, pages 777-785, Stroudsburg, PA.
75. Wainwright, Martin J. and Michael I. Jordan. 2008. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1-2): 1-305.
76. Wang, Sida and Christopher Manning. 2012. Baselines and bigrams: Simple, good sentiment and topic classification. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012), pages 90-94, Jeju Island.
77. Wiebe, Janyce, Theresa Wilson, and Claire Cardie. 2005. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(2-3): 165-210.
78. Williams, Gbolahan K. and Sarabjot Singh Anand. 2009. Predicting the polarity strength of adjectives using Wordnet. In ICWSM, pages 346-349, San Jose, CA.
79. Wilson, Theresa, JanyceWiebe, and Paul Hoffmann. 2009. Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis. Computational Linguistics, 35: 399-433.
80. Yessenalina, Ainur, Yisong Yue, and Claire Cardie. 2010. Multi-level structured models for document-level sentiment classification. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1, 046-1, 056, Cambridge, MA.
81. Younger, Daniel H. 1967. Recognition and parsing of context-free languages in time n3. Information and Control, 10(2): 189-208.
82. Yu, Hong and Vasileios Hatzivassiloglou. 2003. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, EMNLP '03, pages 129-136, Stroudsburg, PA.
83. Zelle, John M. and Raymond J. Mooney. 1996. Learning to parse database queries using inductive logic programming. In AAAI/IAAI, pages 1, 050-1, 055, Portland, OR.
84. Zettlemoyer, Luke S. and Michael Collins. 2007. Online learning of relaxed CCG grammars for parsing to logical form. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL-2007), pages 678-687, Prague.
85. Zettlemoyer, Luke S. and Michael Collins. 2009. Learning context-dependent mappings from sentences to logical form. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2-Volume 2, ACL '09, pages 976-984, Stroudsburg, PA.
86. Zhao, Jichang, Li Dong, Junjie Wu, and Ke Xu. 2012. Moodlens: An emoticon-based sentiment analysis system for Chinese tweets. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '12, pages 1, 528-1, 531, New York, NY.