Abstract
This paper presents a sentiment analysis of Ukrainian tweets on feminism. In order to carry out a computational study of opinions, we have adjusted the SentiStrength algorithm to the Ukrainian language by replacing the English term lists in the program files with the Ukrainian ones. The main contribution is an attempt to compile a social domain sentiment lexicon for Ukrainian (3,736 words). The SentiStength output has shown a prevailing negative sentiment of the analyzed tweets. The program performance was evaluated in terms of accuracy, precision, recall, error, fallout and F1 Score. In addition, we found a number of common attributes of a feminist, which also predominantly express negative attitude. Overall, the findings show that a direct support of a key feminist goal, i.e. equality of women and men in society, by the Ukrainian Tweeter users couples with misconception about the concept of feminism and unwillingness to be called a feminist.
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References
Romanyshyn, M.: Rule-based sentiment analysis of Ukrainian reviews. Int. J. Artif. Intell. Appl. (IJAIA) 4(4), 103 (2013)
Lobur, M., Romaniuk, A., Romanyshyn, M.: Defining an approach for deep sentiment analysis of reviews in Ukrainian. Visnyk Natsionalnogo Universytetu Lvivska Politehnika. Komputerni systemy proektuvannia, Teoria i praktyka 747, pp. 124–130 (2012)
SentiStrength. http://sentistrength.wlv.ac.uk
Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2(1–2), 1–135 (2008)
Liu, B.: Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers, San Rafael (2012)
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)
Strapparava, C., Valitutti, A.: Wordnet-affect: an affective extension of wordnet. In: Proceedings of the 4th International Conference on Language Resources and Evaluation, Lisbon, pp. 1083–1086 (2004)
Agerri, R., GarcÃa-Serrano, A.: Q-WordNet: Extracting polarity from WordNet senses. http://www.lrec-conf.org/proceedings/lrec2010/pdf/2695_Paper.pdf
Baccianella, S., Esuli, A., Sebastiani, F., SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. http://www.lrec-conf.org/proceedings/lrec2010/pdf/2769_Paper.pdf
Turney, P.D.: Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, PA, pp. 417–424 (2002)
Wiebe, J., Wilson, T., Bruce, R., Bell, M., Martin, M.: Learning Subjective Language. Computat. Linguist. 30(3), 277–308 (2004)
Choi, Y., Cardie, C.: Learning with compositional semantics as structural inference for subsentential sentiment analysis. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 793–801 (2008)
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Technol. 61(12), 544–2558 (2012)
Hamilton, W. L., Clark, K., Leskovec, J., Jurafsky, D.: Inducing domain-specific sentiment lexicons from unlabeled corpora. In: Empirical Methods in Natural Language Processing (EMNLP) (2016)
Yang, Y., Eisenstein, J.: Putting things in context: community-specific embedding projections for sentiment analysis. https://www.semanticscholar.org/paper/Putting-Things-in-Context%3A-Community-specific-for-Yang-Eisenstein/17e7efbb17dd1e13c6def85cb6eacf6d0d803e8b
Olson, D.L., Dursun, D.: Advanced Data Mining Techniques, 1st edn. Springer, Heidelberg (2008)
Kis, O.: Who is not protected by the Berehynya, or matriarhy as a male invention. 4(16), 11–16 (2006)
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Levchenko, O., Dilai, M. (2019). Attitudes Toward Feminism in Ukraine: A Sentiment Analysis of Tweets. In: Shakhovska, N., Medykovskyy, M. (eds) Advances in Intelligent Systems and Computing III. CSIT 2018. Advances in Intelligent Systems and Computing, vol 871. Springer, Cham. https://doi.org/10.1007/978-3-030-01069-0_9
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