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Computer Based Stylometric Analysis of Texts in Ukrainian Language

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Artificial Intelligence and Soft Computing (ICAISC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12416))

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Abstract

Stylometry analysis of Slavic-language texts is less explored challenging issue in direction of computational study. The aim of the paper is to develop and verify stylometric methods in a task of authorship, age, and gender of author recognition for literary texts in Ukrainian that could give a usable accuracy. Were prepared common stylistic features using the self-designed corpus. Different feature selection and classification methods were analyzed. Also, the objective of this examination is to analyze several stylometric variables to test its statistical importance with \(\chi ^2\) selection.

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Notes

  1. 1.

    https://www.mustgo.com/worldlanguages/ukrainian/.

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Authors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Anton Mazurko & Tomasz Walkowiak

Authors
  1. Anton Mazurko
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  2. Tomasz Walkowiak
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Corresponding author

Correspondence to Tomasz Walkowiak .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Mazurko, A., Walkowiak, T. (2020). Computer Based Stylometric Analysis of Texts in Ukrainian Language. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2020. Lecture Notes in Computer Science(), vol 12416. Springer, Cham. https://doi.org/10.1007/978-3-030-61534-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-61534-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61533-8

  • Online ISBN: 978-3-030-61534-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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