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Frequent Sets Discovery in Privacy Preserving Quantitative Association Rules Mining Read chapter Read first chapter

2015 | OriginalPaper | Chapter

On Sentiment Polarity Assignment in the Wordnet Using Loopy Belief Propagation

Authors : Marcin Kulisiewicz, Tomasz Kajdanowicz, Przemyslaw Kazienko, Maciej Piasecki

Published in: Hybrid Artificial Intelligent Systems

Publisher: Springer International Publishing

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Abstract

Sentiment analysis is a very active and nowadays highly addressed research area. One of the problem in sentiment analysis is text classification in terms of its attitude, especially in reviews or comments from social media. In general, this problem can be solved by two different approaches: machine learning methods and based on lexicons. Methods based on lexicons require properly prepared lexicons which usually are obtained manually from experts and it costs a lot in terms of time and resources. This paper aims at automatic lexicon creation for sentiment analysis. There are proposed the methods based on Loopy Belief Propagation that starting from small set of seed words with a priori known sentiment value propagates the sentiment to whole Wordnet.

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previous chapter Exemplar Selection Using Collaborative Neighbor Representation
next chapter Evaluation of Relative Indexes for Multi-objective Clustering
Literature
1.
2.
Das, S., Chen, M.: Yahoo! for amazon: extracting market sentiment from stock message boards. Proc. Asia Pac. financ. Assoc. Ann. Conf. (APFA) 35, 43 (2001)
3.
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, pp. 417–422 (2006)
4.
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. ACM (2004)
5.
Huettner, A., Subasic, P.: Fuzzy typing for document management. In: ACL 2000 Companion Volume: Tutorial Abstracts and Demonstration Notes, pp. 26–27 (2000)
6.
Jindal, N., Liu, B.: Review spam detection. In: WWW 2007: Proceedings of the 16th International Conference on World Wide Web, pp. 1189–1190. ACM Press (2007)
7.
Jurafsky, D., Manning, C.: Sentiment analysis, natural language processing. In: Coursera.com (2014)
8.
Kazienko, P., Kajdanowicz, T.: Label-dependent node classification in the network. Neurocomput. 75(1), 199–209 (2012)CrossRef
9.
Kim, S.M., Hovy, E.: Extracting opinions, opinion holders, and topics expressed in online news media text. In: Proceedings of the Workshop on Sentiment and Subjectivity in Text, SST 2006, Association for Computational Linguistics pp. 1–8, Stroudsburg (2006)
10.
Lerman, K., Blair-goldensohn, S., Mcdonald, R.: Sentiment summarization: evaluating and learning user preferences. In: Proceedings of the European Chapter of the Association for Computational Linguistics EACL, pp. 514–522 (2009)
11.
McAuley, J.J., Leskovec, J.: From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 897–908. International World Wide Web Conferences Steering Committee / ACM (2013)
12.
Murphy, K.P., Weiss, Y., Jordan, M.I.: Loopy belief propagation for approximate inference: an empirical study. In: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, UAI 1999, pp. 467–475 (1999)
13.
Raez, A.M., Martinez-Camara, E., Martin-Valdivia, M.T., Urena-Lopez, L.A.: Ranked wordnet graph for sentiment polarity classification in twitter. Comput. Speech Lang. 28(1), 93–107 (2014)CrossRef
14.
Sehgal, V., Song, C.: Sops: stock prediction using web sentiment. In: Seventh IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007, pp. 21–26. IEEE (2007)
15.
Turney, P.D., Littman, M.L.: Measuring praise and criticism: inference of semantic orientation from association. ACM Trans. Inf. Syst. 21(4), 315–346 (2003)CrossRef
16.
Valitutti, A., Strapparava, C., Stock, O.: Developing affective lexical resources. PsychNology J. 2(1), 61–83 (2004)
Metadata
Title
On Sentiment Polarity Assignment in the Wordnet Using Loopy Belief Propagation
Authors
Marcin Kulisiewicz
Tomasz Kajdanowicz
Przemyslaw Kazienko
Maciej Piasecki
Copyright Year
2015
Book
Hybrid Artificial Intelligent Systems

Print ISBN: 978-3-319-19643-5

Electronic ISBN: 978-3-319-19644-2

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-19644-2_38

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