Abstract
This study develops an automatic method for in-depth sentiment analysis of movie review documents using information extraction techniques and a machine learning approach. The analysis results provide sentiment orientations in multiple perspectives, each focusing on a specific aspect of the reviewed entity. Sentiment classification in multiple perspectives can provide more comprehensive sentiment analysis for applications like sentiment ranking and rating. By utilizing information extraction techniques such as entity extraction, co-referencing and pronoun resolution, the review texts are segmented into sections where each section discusses particular aspect of the reviewed entity. For each section of sentences, Support Vector Machine (SVM) using vectors of terms is applied to determine sentiment orientation toward the target aspect. In our exploratory study, we focus on the sentiment orientations toward overall movie, movie directors and casts in the movie. The experimental results prove the effectiveness of the proposed approach for sentiment classification of movie reviews.
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References
Bontcheva, K., Tablan, V., Maynard, D., Cunningham, H.: Evolving GATE to Meet New Challenges in Language Engineering. Natural Language Engineering 10(3-4), 349–373 (2004)
Byrt, T.: How Good Is That Agreement? Epidemiology, vol. 7, p. 561 (1996)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 168–177 (2004)
Joachims, T.: Text categorization with support vector machines: Learning with many relevant features. In: Proceedings of 10th European Conference on Machine-learning, Chemnitz, Germany, April 21–24, pp. 137–142 (1998)
Jones, K.S., Willet, P.: Readings in Information Retrieval. Morgan Kaufman, San Francisco (1997)
Zhuang, L., Jing, F., Zhu, X.-Y.: Movie review mining and summarization. In: Proceeding of the 15th ACM Conference on Information and Knowledge Management, pp. 43–50 (2006)
Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment classification using machine-learning techniques. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing, pp. 79–86 (2002)
Pang, B., Lee, L.: A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics ACL, Barcelona, Spain, 271-278 (2004)
Sebastiani, F.: Machine-learning in automated text categorization. ACM Computing Surveys 34(1), 1–47 (2002)
Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications. In: Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistic (2002)
Snyder, B., Barzilay, R.: Multiple aspects ranking using the good grief algorithm. In: Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT-NAACL), pp. 300–307 (2007)
Turney, P.D.: 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, pp. 417–434. Philadelphia (2002)
Witten, I.H., Bainbridge, D.I.: How to build a digital library. Morgan Kaufmann, San Francisco (2003)
Yi, J., Nasukawa, T., Bunescu, R., Niblack, W.: Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques. In: Proceedings of the Third IEEE International Conference on Data Mining ICDM, pp. 427–434 (2003)
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© 2008 Springer-Verlag Berlin Heidelberg
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Thet, T.T., Na, JC., Khoo, C.S.G. (2008). Sentiment Classification of Movie Reviews Using Multiple Perspectives. In: Buchanan, G., Masoodian, M., Cunningham, S.J. (eds) Digital Libraries: Universal and Ubiquitous Access to Information. ICADL 2008. Lecture Notes in Computer Science, vol 5362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89533-6_19
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DOI: https://doi.org/10.1007/978-3-540-89533-6_19
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