Sentiment analysis of textual reviews: Evaluating machine learning, unsupervised and sentiwordnet approaches

Proceedings of the 2013 5th International Conference on Knowledge and Smart Technology, KST 2013

Volumn , Issue , 2013, Pages 122-127

  Singh, V K ^a   Piryani, R ^a   Uddin, A ^a   Waila, P ^b   Marisha, ^b  

^a SOUTH ASIAN UNIVERSITY   (India)

^b BANARAS HINDU UNIVERSITY   (India)

Author keywords

Na ve Bayes; Semantic Orientation Approach; Sentiment Analysis; SentiWordNet; Support Vector Machine

Indexed keywords

INFORMATION RETRIEVAL SYSTEMS; LARGE DATASET; SEMANTICS; SENTIMENT ANALYSIS; SUPPORT VECTOR MACHINES;

LARGE DATASETS; MOVIE REVIEWS; SEMANTIC ORIENTATION APPROACH; SENTIMENT CLASSIFICATION; SENTIWORDNET; TWO MACHINES;

LEARNING SYSTEMS;

EID: 85094619750     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/KST.2013.6512800     Document Type: Conference Paper

References (21)

1. V. K. Singh, M. Mukherjee & G. K. Mehta, "Combining Collaborative Filtering and Sentiment Analysis for Improved Movie Recommendations", In C. Sombattheera et. al. (Eds.): Multi-disciplinary Trends in Artificial Intelligence, LNAI 7080, Springer-Verlag, Berlin-Heidelberg, pp. 38-50, 2011.
2. V. K. Singh, M. Mukherjee & G. K. Mehta, "Combining a Content Filtering Heuristic and Sentiment Analysis for Movie Recommendations", In K.R. Venugopal & L.M. Patnaik (Eds.): ICIP 2011, Aug. 2011, CCIS 157, pp. 659-664, Springer, Heidelberg, 2011.
3. K. Dave, S. Lawerence & D. Pennock," Mining the Peanut Gallery-Opinion Extraction and Semantic Classification of Product Reviews", Proceedings of the 12th International World Wide Web Conference, pp. 519-528, 2003.
4. P. Turney, "Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews", Proceedings of ACL-02, 40th Annual Meeting of the Association for Computational Linguistics, pp. 417-424, Philadelphia, US, 2002.
5. A. Esuli & F. Sebastiani, "Determining the Semantic Orientation of terms through gloss analysis", Proceedings of CIKM-05, 14th ACM International Conference on Information and Knowledge Management, pp. 617-624, Bremen, DE, 2005.
6. B. Pang, L. Lee & S. Vaithyanathan, "Thumbs up? Sentiment classificationusing machine learning techniques", Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 79-86, Philadelphia, US, 2002.
7. S.M. Kim & E. Hovy, "Determining sentiment of opinions", Proceedings of the COLING Conference, Geneva, 2004.
8. K.T. Durant& M.D. Smith, "Mining Sentiment Classification from Political Web Logs", Proceedings of WEBKDD'06, ACM, 2006.
9. F. Sebastiani, "Machine Learning in Automated text categorization", ACM Computing Surveys, 34(1): 1-47, 2002.
10. P. Turney& M.L. Littman, "Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word corpus", NRC Publications Archive, 2002.
11. C.D. Manning, P. Raghavan & H. Schutze, "Introduction to Information Retrieval", Cambridge University Press, New York, USA, 2008.
12. V. K. Singh, M. Mukherjee, G. K. Mehta, N. Tiwari&S. Garg, "Opinion Mining from Weblogs and its Relevance for Sociopolitical Research", In M. Natarajanet. al. (Eds.) Advances in Computer Science and Information Technology. Part II, LNICST 85, Springer, pp. 134-145, 2012.
13. Weka D ata M ining S oftware i n J AVA, http://www.cs.waikato.ac.nz/ml/weka/
14. B. Liu, "Web Data Mining: Exploring Hyperlinks, Contents and Usage Data", Springer-Verlag, Berlin-Heidelberg, pp. 411-416, 2002.
15. V. K. Singh, M. Mukherjee & G. K. Mehta, "Sentiment and Mood Analysis of Weblogs using POS Tagging based Approach", In S. Aluru et al. (Eds.): IC3 2011, CCIS 168, pp. 313-324, Springer- Verlag, Berlin Heidelberg, 2011.
16. SentiWordNet, available at http://www.sentiwordnet.isti.cnr.it
17. F. Benamara, C. Cesarano& D. Reforigiato, "Sentiment Analysis: Adjectives and Adverbs are better than Adjectives Alone", Proceedings of ICWSM 2006, CO USA, 2006.
18. http://www.cs.cornell.edu/people/pabo/movie-review-data/
19. Internet Movie Database, http://www.imdb.com
20. P. Chaovalit & L. Zhou, "Movie Review Mining: Comparison between Supervised and Unsupervised Approaches", Proceedings of the 38th Hawaii International Conference on System Sciences, 2005.
21. P. Waila, Marisha, V.K. Singh & M.K. Singh, "Evaluating Machine Learning and Unsupervised Semantic Orientation Approaches for Sentiment Analysis of Textual Reviews", Proceedings of International Conference on Computational Intelligence and Computing Research, Coimbatore, India, 2012.