In:From Text to Political Positions: Text analysis across disciplines
Edited by Bertie Kaal, Isa Maks and Annemarie van Elfrinkhof
[Discourse Approaches to Politics, Society and Culture 55] 2014
► pp. 117–134
Sentiment Analysis in Parliamentary Proceedings
Published online: 7 May 2014
https://doi.org/10.1075/dapsac.55.06gri
https://doi.org/10.1075/dapsac.55.06gri
This chapter addresses the question whether opinion-mining techniques can successfully be used to automatically retrieve political viewpoints from parliamentary proceedings. Two specific preprocessing tasks were identified and systematically evaluated: automatically determining subjectivity in the publications and automatically determining the semantic orientation of the subjective parts. A corpus of recent parliamentary proceedings was collected and a gold standard annotation was created on both subjectivity and orientation. Following this, a number of models based on subjectivity lexicons and machine-learning algorithms were evaluated. Machine-learning algorithms perform best, but methods based on subjectivity lexicons also provide promising results. Based on these results we can conclude that opinion-mining techniques applied to political data score just as well as the state of the art in other more traditional domains of opinion mining like product reviews and blogs.
References (33)
Banea, C., R. Mihalcea, and J. Wiebe. 2008. A bootstrapping method for building subjectivity lexicons for languages with scarce resources. LREC 2008.
Chesley, P., B. Vincent, L. Xu, and R. Srihari. 2006. Using Verbs and Adjectives to Automatically Classify Blog Sentiment. AAAI Spring Symposium Technical Report SS-06-03.
Compact Oxford English Dictionary: opinion. (n.d.). (O. U. Press, Producer) Retrieved 06 05, 2009 from Compact Oxford English Dictionary: [URL]
Ding, X., and B. Liu. 2007. The utility of linguistic rules in opinion mining. Proceedings of the 30th Annual international ACM SIGIR Conference on Research and Development in information Retrieval, pp. 811–812. Amsterdam: ACM, New York, NY.
Edens, J., M. Liem., T. Mensink, R. Weve, and L. van Zande. 2006. Measuring Politics. University of Amsterdam, Amsterdam.
Esuli, A. and F. Sebastiani. 2006. Determining term subjectivity and term orientation for opinion mining. Proceedings of the Eleventh Conference on European Chapter of the Association for Computational Linguistics. Trento, Italy: European Chapter Meeting of the ACL. Association for Computational Linguistics., pp. 193–200.
Furuse, O., N. Hiroshima, S. Yamada, and R. Kataoka. 2007. Opinion sentence search engine on open-domain blog. Proceedings of the 20th International Joint Conference of Artificial Intelligence (IJCAI2007).
Jijkoun, V. and K. Hofmann. 2009. Generating a non-English subjectivity lexicon: Relations that matter. Second Conference of the European Chapter of the Association for Computational Linguistics (EACL-09).
Kamps, J. and M. Marx. 2001. Words with attitude. 1st International WordNet Conference, pp. 332–341.
Kim, S.-M. and E. Hovy. 2004. Determining the sentiment of opinions. Proceedings of
COLING-04, pp. 1367–1373. Geneva, Switzerland.
Kim, S.-M. and E.H. Hovy. 2005. Automatic detection of opinion bearing words and sentences. Second International Joint Conference on Natural Language Processing.
Ku, L., Y. Liang, and H. Chen. 2006 Tagging heterogeneous evaluation corpora for opinionated tasks. LREC 2006.
Manning, C., P. Raghavan, and H. Schütze. 2008. Introduction to Information Retrieval. Cambridge: Cambridge University Press.
Marx, M., N. Aders and A. Schuth. 2010. Digital sustainable publication of legacy parliamentery proceedings. In Proceedings dg.o 2010.
Marx, M. and A. Schuth. 2010. DutchParl. A corpus of parliamentary proceedings in Dutch. In Proceedings LREC 2010. pp. 3670–3677.
McKeown, K. and V. Hatzivassiloglou. 1997. Predicting the semantic orientation of adjectives. Proceedings of the 35th annual meeting of ACL.
Mishne, G. 2005. Experiments with mood classification in blog posts. 1st Workshop on Stylistic Analysis Of Text For Information Access.
Mullen, T. and R. Malouf. 2006. A preliminary investigation into sentiment analysis of informal political discourse. AAAI Symposium on Computational Approaches to Analysing Weblogs (AAAI-CAAW), pp. 159–162.
Osgood, C., G. Suci, and P. Tannenbaum. 1957. The measurement of meaning. Urbana, IL: University of Illinois Press.
Osman, D. and J. Yearwood. 2007. Opinion search in web logs.
Proceedings of the Eighteenth Conference on Australasian Database, 63
. Ballarat, Victoria, Australia.
Pang, B. and L. Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends® in Information Retrieval, 2 (1-2), pp. 1–135.
Riloff, E. and J. Wiebe. 2003. Learning extraction patterns for subjective expressions. Conference on Empirical Methods in Natural Language Processing (EMNLP-03), pp. 105–112.
TreeTagger 3.2. (n.d.). From TreeTagger 3.2: [URL]
Turney, P. 2001. Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews.
Proceedings of the 40th Annual Meeting on Association For Computational Linguistics
pp. 417–424. Philadelphia, Pennsylvania: Annual Meeting of the ACL. Association for Computational Linguistics, Morristown, NJ.
Turney, P. and M. Littman. 2003. Measuring praise and criticism: Inference of semantic orientation from association. ACM Trans. Inf. Syst., 21(4), pp. 315–346.
Tweede Kamer: Plenaire vergaderingen. (n.d.). Retrieved 06 03, 2009 from Tweede Kamer der Staten Generaal: [URL]
Van Dale online dictionary: mening. (n.d.). (V. Dale, Producer) Retrieved 06 05, 2009 from Mening: [URL]
WekaWiki: Primer. (n.d.). Retrieved 06 10, 2009 from Weka-Machine Learning Software in Java: [URL]
Wiebe, J.M., R.F. Bruce, and T.P. O’Hara. 1999. Development and use of a gold-standard data set for subjectivity classifications. Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics, pp. 246–253. College Park, Maryland: Association for Computational Linguistics.
Wiebe, J. and E. Riloff. 2005. Creating subjective and objective sentence classifiers from unannotated texts. In Computational Linguistics and Intelligent Text Processing Vol. 3406/2005, pp. 486–497. Heidelberg: Springer.
Wilson, T., D. Pierce, and J. Wiebe. 2003. Identifying opinionated sentences. Proceedings of the 2003 Conference of the North American Chapter of the Association For Computational Linguistics on Human Language Technology:Demonstrations. 4, pp. 33–34. Edmonton, Canada: North American Chapter of the Association for Computational Linguistics.
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