Abstract
In this paper we tackle an opinion extraction (OE) task, i.e., identifying in a text each expression of subjectivity, the subject expressing it, and its possible target. We especially focus on how lexical resources specifically developed for opinion mining could be used to improve the performance of an opinion extraction system. We report results, complete with statistical significance tests and inter-annotator agreement data, on two manually annotated corpora, one of English and one of Italian texts. We evaluate our results using standard evaluation measures and also using a new evaluation measure we have recently proposed.
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References
Breck, E., Choi, Y., Cardie, C.: Identifying expressions of opinion in context. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), Hyderabad, IN, pp. 2683–2688 (2007)
Choi, Y., Breck, E., Cardie, C.: Joint extraction of entities and relations for opinion recognition. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), Sydney, AU (2006)
Choi, Y., Cardie, C., Riloff, E., Patwardhan, S.: Identifying sources of opinions with conditional random fields and extraction patterns. In: Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP 2005), Vancouver, CA, pp. 355–362 (2005)
Kim, S.M., Hovy, E.: Identifying opinion holders for question answering in opinion texts. In: Proceedings of the AAAI 2005 Workshop on Question Answering in Restricted Domains, Pittsburgh, US (2005)
Kim, S.M., Hovy, E.: Extracting opinions, opinion holders, and topics expressed in online news media text. In: Proceedings of ACL/COLING 2006 Workshop on Sentiment and Subjectivity in Text, Sidney, AUS (2006)
Wiebe, J., Breck, E., Buckley, C., Cardie, C., Davis, P., Fraser, B., Litman, D., Pierce, D., Riloff, E., Wilson, T., Day, D., Maybury, M.: Recognizing and organizing opinions expressed in the world press. In: Proceedings of the 2003 AAAI Spring Symposium on New Directions in Question Answering, Stanford, US, pp. 12–19 (2003)
Wiebe, J., Wilson, T., Cardie, C.: Annotating expressions of opinions and emotions in language. Language Resources and Evaluation 39(2/3), 165–210 (2005)
Esuli, A., Sebastiani, F.: SentiWordNet: A publicly available lexical resource for opinion mining. In: Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), Genova, IT, pp. 417–422 (2006)
Esuli, A., Sebastiani, F., Urciuoli, I.: Annotating expressions of opinion and emotion in the Italian Content Annotation Bank. In: Proceedings of the 6th Conference on Language Resources and Evaluation (LREC 2008), Marrakech, MA (2008)
Esuli, A., Sebastiani, F.: Evaluating information extraction. In: Agosti, M., Ferro, N., Peters, C., de Rijke, M., Smeaton, A. (eds.) CLEF 2010. LNCS, vol. 6360, pp. 100–111. Springer, Heidelberg (2010)
Riloff, E.: Automatically generating extraction patterns from untagged text. In: Proceedings of the 13th Conference of the American Association for Artificial Intelligence (AAAI 1996), Portland, US, pp. 1044–1049 (1996)
Kudo, T., Matsumoto, Y.: Fast methods for kernel-based text analysis. In: Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL 2003), Sapporo, JP, pp. 24–31 (2003)
Stone, P.J., Dunphy, D.C., Smith, M.S., Ogilvie, D.M.: The General Inquirer: A Computer Approach to Content Analysis. The MIT Press, Cambridge (1966)
Hatzivassiloglou, V., McKeown, K.R.: Predicting the semantic orientation of adjectives. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL 1997), Madrid, ES, pp. 174–181 (1997)
Esuli, A., Sebastiani, F.: Random-walk models of term semantics: An application to opinion-related properties. In: Proceedings of the 3rd Language Technology Conference (LTC 2007), Poznań, PL, pp. 221–225 (2007)
Magnini, B., Pianta, E., Girardi, C., Negri, M., Romano, L., Speranza, M., Bartalesi-Lenzi, V., Sprugnoli, R.: I-CAB: The Italian content annotation bank. In: Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), Genova, IT, pp. 963–968 (2006)
Freitag, D.: Using grammatical inference to improve precision in information extraction. In: Proceedings of the ICML 1997 Workshop on Grammatical Inference, Automata Induction, and Language Acquisition, Nashville, TN (1997)
Lavelli, A., Califf, M.E., Ciravegna, F., Freitag, D., Giuliano, C., Kushmerick, N., Romano, L., Ireson, N.: Evaluation of machine learning-based information extraction algorithms: Criticisms and recommendations. Language Resources and Evaluation 42(4), 361–393 (2008)
Pianta, E., Bentivogli, L., Girardi, C.: MultiWordNet: Developing an aligned multilingual database. In: Proceedings of the 1st International Conference on Global WordNet (GWN 2002), Mysore, IN (2002)
Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd ACM International Conference on Research and Development in Information Retrieval (SIGIR 1999), Berkeley, US, pp. 42–49 (1999)
Spiegel, M.R., Stephens, L.J.: Statistics, 3rd edn. McGraw-Hill, New York (1999)
Cohen, J.: A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20(1), 37–46 (1960)
Eugenio, B.D., Glass, M.: The kappa statistic: A second look. Computational Linguistics 30(1), 95–101 (2004)
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Esuli, A., Sebastiani, F. (2011). Enhancing Opinion Extraction by Automatically Annotated Lexical Resources. In: Vetulani, Z. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2009. Lecture Notes in Computer Science(), vol 6562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20095-3_46
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DOI: https://doi.org/10.1007/978-3-642-20095-3_46
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