Skip to main content

Sentiment Analysis in Polish Web-Political Discussions

  • 472 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10930)

Abstract

The article presents analysis of Polish Internet political discussion forums, characterized by significant polarization and high levels of emotion. The study compares samples of discussions gathered from the Internet comments concerning the last Polish election candidates. The authors compare three dictionary based sentiment analysis methods (built using different sentiment lexicons) with two machine learning ones, and explore methods using word embeddings to enhance sentiment analysis using dictionary based algorithms. The best performing algorithm is giving results closely corresponding to human evaluations.

Keywords

  • Text classification
  • Sentiment analysis
  • Machine learning

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-93782-3_26
  • Chapter length: 15 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   69.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-93782-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   89.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.

Notes

  1. 1.

    Datasets are available on http://opi-lil.github.io/datasets/website.

References

  1. Baumeister, R.F., Bratslavsky, E., Finkenauer, C., Vohs, K.D.: Bad is stronger than good. Rev. Gen. Psychol. 5(4), 323 (2001)

    CrossRef  Google Scholar 

  2. Bermingham, A., Smeaton, A.F.: On using twitter to monitor political sentiment and predict election results (2011)

    Google Scholar 

  3. Durant, K.T., Smith, M.D.: Mining sentiment classification from political web logs. In: Proceedings of Workshop on Web Mining and Web Usage Analysis of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (WebKDD-2006), Philadelphia, PA (2006)

    Google Scholar 

  4. Greene, W.H.: The econometric approach to efficiency analysis. In: The Measurement of Productive Efficiency and Productivity Growth, pp. 92–250 (2008)

    CrossRef  Google Scholar 

  5. Huang, E.H., Socher, R., Manning, C.D., Ng, A.Y.: Improving word representations via global context and multiple word prototypes. In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers, vol. 1, pp. 873–882. Association for Computational Linguistics (2012)

    Google Scholar 

  6. Kiritchenko, S., Zhu, X., Mohammad, S.M.: Sentiment analysis of short informal texts. J. Artif. Intell. Res. 50(1), 723–762 (2014)

    Google Scholar 

  7. MacKuen, M., Wolak, J., Keele, L., Marcus, G.E.: Civic engagements: resolute partisanship or reflective deliberation. Am. J. Polit. Sci. 54(2), 440–458 (2010)

    CrossRef  Google Scholar 

  8. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)

  9. Mullen, T., Malouf, R.: A preliminary investigation into sentiment analysis of informal political discourse. In: AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, pp. 159–162 (2006)

    Google Scholar 

  10. Mutz, D.C.: Facilitating communication across lines of political difference: the role of mass media. In: American Political Science Association, vol. 95, pp. 97–114. Cambridge Univ Press (2001)

    Google Scholar 

  11. Paltoglou, G., Gobron, S., Skowron, M., Thelwall, M., Thalmann, D.: Sentiment analysis of informal textual communication in cyberspace. In: Proceedings of the Engage 2010, Springer LNCS State-of-the-Art Survey, pp. 13–25 (2010)

    Google Scholar 

  12. Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retrieval 2(1–2), 1–135 (2008)

    CrossRef  Google Scholar 

  13. Peeters, G., Czapinski, J.: Positive-negative asymmetry in evaluations: the distinction between affective and informational negativity effects. Eur. Rev. Soc. Psychol. 1(1), 33–60 (1990)

    CrossRef  Google Scholar 

  14. Ptaszynski, M., Masui, F., Rzepka, R., Araki, K.: Emotive or non-emotive: that is the question. In: ACL 2014, p. 59 (2014)

    Google Scholar 

  15. Rainie, L., Horrigan, J.: Election 2006 online (2007)

    Google Scholar 

  16. Russell, S., Norvig, P.: Artificial intelligence: a modern approach (1995)

    Google Scholar 

  17. Sobkowicz, A.: Automatic sentiment analysis in polish language. In: Ryżko, D., Gawrysiak, P., Kryszkiewicz, M., Rybiński, H. (eds.) Machine Intelligence and Big Data in Industry. SBD, vol. 19, pp. 3–10. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-30315-4_1

    CrossRef  Google Scholar 

  18. Sobkowicz, P., Sobkowicz, A.: Two-year study of emotion and communication patterns in a highly polarized political discussion forum. Soc. Sci. Comput. Rev. 30(4), 448–469 (2012)

    CrossRef  Google Scholar 

  19. Stieglitz, S., Dang-Xuan, L.: Political communication and influence through microblogging-an empirical analysis of sentiment in twitter messages and retweet behavior. In: 2012 45th Hawaii International Conference on System Science (HICSS), pp. 3500–3509. IEEE (2012)

    Google Scholar 

  20. Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Tech. 61(12), 2544–2558 (2010)

    CrossRef  Google Scholar 

  21. Wojcieszak, M.: “Don’t talk to me”: effects of ideologically homogeneous online groups and politically dissimilar offline ties on extremism. New Media Soc. 12, 637–655 (2010)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antoni Sobkowicz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Sobkowicz, A., Kozłowski, M. (2018). Sentiment Analysis in Polish Web-Political Discussions. In: Vetulani, Z., Mariani, J., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2015. Lecture Notes in Computer Science(), vol 10930. Springer, Cham. https://doi.org/10.1007/978-3-319-93782-3_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-93782-3_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93781-6

  • Online ISBN: 978-3-319-93782-3

  • eBook Packages: Computer ScienceComputer Science (R0)