Baselines and bigrams: Simple, good sentiment and topic classification

50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference

Volumn 2, Issue , 2012, Pages 90-94

  Wang, Sida ^a   Manning, Christopher D ^a  

^a Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BASELINE METHODS; BIGRAMS; FEATURE VALUES; NAIVE BAYES; SENTIMENT ANALYSIS; STATE-OF-THE-ART PERFORMANCE; TEXT CLASSIFICATION; TOPIC CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS; DATA MINING;

SUPPORT VECTOR MACHINES;

EID: 84875872773     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. R. Collobert and J. Weston. 2008. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proceedings of ICML.
2. George E. Dahl, Ryan P. Adams, and Hugo Larochelle. 2012. Training restricted boltzmann machines on word observations. arXiv:1202.5695v1 [cs.LG].
3. Rong-En Fan, 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, June.
4. Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings ACM SIGKDD, pages 168-177.
5. Alistair Kennedy and Diana Inkpen. 2006. Sentiment classification of movie reviews using contextual valence shifters. Computational Intelligence, 22.
6. Simon Lacoste-Julien, Fei Sha, and Michael I. Jordan. 2008. DiscLDA: Discriminative learning for dimensionality reduction and classification. In Proceedings of NIPS, pages 897-904.
7. Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011. Learning word vectors for sentiment analysis. In Proceedings of ACL.
8. Justin Martineau and Tim Finin. 2009. Delta tfidf: An improved feature space for sentiment analysis. In Proceedings of ICWSM.
9. Andrew McCallum and Kamal Nigam. 1998. A comparison of event models for naive bayes text classification. In AAAI-98 Workshop, pages 41-48.
10. Vangelis Metsis, Ion Androutsopoulos, and Georgios Paliouras. 2006. Spam filtering with naive bayes - which naive bayes? In Proceedings of CEAS.
11. Karo Moilanen and Stephen Pulman. 2007. Sentiment composition. In Proceedings of RANLP, pages 378- 382, September 27-29.
12. Tetsuji Nakagawa, Kentaro Inui, and Sadao Kurohashi. 2010. Dependency tree-based sentiment classification using CRFs with hidden variables. In Proceedings of ACL: HLT.
13. Andrew Y Ng and Michael I Jordan. 2002. On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes. In Proceedings of NIPS, volume 2, pages 841-848.
14. Bo Pang and Lillian Lee. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proceedings of ACL.
15. Bo Pang and Lillian Lee. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of ACL.
16. Jason D. Rennie, Lawrence Shih, Jaime Teevan, and David R. Karger. 2003. Tackling the poor assumptions of naive bayes text classifiers. In Proceedings of ICML, pages 616-623.
17. Greg Schohn and David Cohn. 2000. Less is more: Active learning with support vector machines. In Proceedings of ICML, pages 839-846.
18. Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning. 2011. Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions. In Proceedings of EMNLP.
19. Casey Whitelaw, Navendu Garg, and Shlomo Argamon. 2005. Using appraisal taxonomies for sentiment analysis. In Proceedings of CIKM-05.
20. Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(2- 3):165-210.