Exploring Feature Definition and Selection for Sentiment Classifiers

Proceedings of the 5th International AAAI Conference on Weblogs and Social Media, ICWSM 2011

Volumn , Issue , 2011, Pages 546-549

  Mejova, Yelena ^a   Srinivasan, Padmini ^a,b  

^a University of Iowa   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE SELECTION;

FEATURES SELECTION; LARGE DATASETS; MOVIE REVIEWS; MUTUAL INFORMATIONS; N-GRAMS; PART OF SPEECH; POLARITY CLASSIFICATION; PRODUCT REVIEWS; SMALL DATA SET; TERM FREQUENCY;

CLASSIFICATION (OF INFORMATION);

EID: 85167463061     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Benamara, F.; Cesarano, C.; Picariello, A.; Reforgiato, D.; and Subrahmanian, V. 2007. Sentiment analysis: Adjectives and adverbs are better than adjectives alone. Proc. of ICWSM.
2. Blitzer, J.; Dredze, M.; and Pereira, F. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. ACL 440–447.
3. Chesley, P.; Vincent, B.; Xu, L.; and Srihari, R. K. 2006. Using verbs and adjectives to automatically classify blog sentiment. Proceedings of the AAAI Spring Symposium on Computational Approaches to Analyzing Weblogs.
4. Das, S., and Chen, M. 2001. Yahoo! for amazon: Extracting market sentiment from stock message boards. Proc. of APFA.
5. Dave, K.; Lawrence, S.; and Pennock, D. M. 2003. Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. Proc. of WWW.
6. Esuli, A., and Sebastiani, F. 2006. Sentiwordnet: A publicly available lexical resource for opinion mining. Proc. of LREC.
7. Jindal, N., and Liu, B. 2007. Review span detection. WWW.
8. Li, S., and Zong, C. 2008. Multi-domain sentiment classification. HLT-Short’08 Proc. of ACL on Human Language Technologies.
9. Mejova, Y. 2010. Tapping into sociological lexicons for sentiment polarity classification. Young Scientists Conference, RuSSIR’10.
10. Paltoglou, G., and Thelwall, M. 2010. A study of information retrieval weighting schemes for sentiment analysis. Proc. of ACL 1386–1395.
11. Pang, B., and Lee, L. 2002. Thumbs up?: sentiment classification using machine learning techniques. Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing 10:79–86.
12. Pang, B., and Lee, L. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. Proc. of ACL.
13. Platt, J. C. 1998. Fast training of support vector machines using sequential minimal optimization. Advances in Kernel Methods - Support Vector Learning.
14. Strapparava, C., and Vlitutti, A. 2004. Wordnet-affect: and affective extension of wordnet. Proc. of LREC.
15. Wiebe, J. M.; Wilson, T.; Bruce, R.; Bell, M.; and Martin, M. 2004. Learning subjective language. Computational Linguistics 30.