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Opinion Analysis from the Social Web Contributions

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6922))

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Abstract

The paper focuses on the automatic opinion analysis related to web discussions. It introduces a method for solving basic problems of opinion analysis (determination of word subjectivity, polarity as well as intensity of this polarity). The method solves the reversion of polarity by negation as well as determination of polarity intensity of word combinations. A dynamic coefficient for the word combinations processing is introduced and an implementation of the method is presented. In addition, the paper describes test results of the presented implementation and discussion of these results as well.

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References

  1. Barla, M., Bieliková, M.: On Deriving Tagsonomies: Keyword Relations Coming from Crowd. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS(LNAI), vol. 5796, pp. 309–320. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  2. Catena, A., Alexandrov, M., Ponomareva, N.: Opinion Analysis of Publications on Economics with a Limited Vocabulary of Sentiments. International Journal on Social Media. MMM: Monitoring, Measurement, and Mining 1(1), 20–31 (2010)

    Google Scholar 

  3. Ding, X., Liu, B., YuA, P.: Holistic Lexicon-Based Approach to Opinion Mining. In: Proc. of the Int. Conf. on Web Search and Web Data Mining WSDM 2008, New York, NY, USA, pp. 231–240 (2008)

    Google Scholar 

  4. Heer, J., Boyd, D.: Vizster: Visualizing Online Social Networks. In: Proceedings of the IEEE Symposium on Information Visualization INFOVIS 2005, Washington, USA, pp. 5–13 (2005)

    Google Scholar 

  5. Kaurova, O., Alexandrov, M., Ponomareva, N.: The Study of Sentiment Word Granularity for Opinion Analysis (a Comparison with Maite Taboada Works). International Journal on Social Media. MMM: Monitoring, Measurement, and Mining 1(1), 45–57 (2010)

    Google Scholar 

  6. Lukáč, G., Butka, P., Mach, M.: Semantically-enhanced extension of the discussion analysis algorithm in SAKE. In: SAMI 2008, 6th International Symposium on Applied Machine Intelligence and Informatics, Herľany, Slovakia, pp. 241–246 (January 2008)

    Google Scholar 

  7. Machová, K., Krajč, M.: Opinion Classification in Threaded Discussions on the Web. In: Proc. of the 10th Annual International Conference Znalosti 2011, Stará Lesná, pp. 136–147. FEI Technická univerzita Ostrava, Czech Republic (2011)

    Google Scholar 

  8. Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. Foundation and Trends in Information Retrieval 2(1-2), 1–135 (2008)

    Google Scholar 

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Machová, K. (2011). Opinion Analysis from the Social Web Contributions. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_35

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  • DOI: https://doi.org/10.1007/978-3-642-23935-9_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23934-2

  • Online ISBN: 978-3-642-23935-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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