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Title: Numerals in authorial Turkish-language texts and the stylometric analysis
Authors: Zenkov, A.
Zenkov, E.
Zenkov, M.
Sazanova, L.
Issue Date: 2021
Publisher: EDP Sciences
Citation: Numerals in authorial Turkish-language texts and the stylometric analysis / A. Zenkov, E. Zenkov, M. Zenkov, et al. — DOI 10.1051/e3sconf/202127001038 // E3S Web of Conferences. — 2021. — Vol. 270. — 01038.
Abstract: Two approaches to the statistical analysis of texts are suggested, both based on the study of numerals occurrence in coherent texts. The first approach is related to the study of the frequency distribution of various leading digits of numerals occurring in the text. These frequencies are unequal: the digit 1 is strongly dominating; usually, the incidence of subsequent digits is monotonically decreasing. The frequencies of occurrence of the digit 1, as well as, to a lesser extent, the digits 2 and 3, are usually a characteristic author's style feature, manifested in all (sufficiently long) texts of any author. This approach is convenient for testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach is the extension of the first one and requires the study of the frequency distribution of numerals themselves (not their leading digits). The approach yields non-trivial information about the author, stylistic and genre peculiarities of the texts and is suited for the advanced discourse analysis. This paper deals with the application of the second approach to the literary texts in Turkish. We have analysed almost the whole corpus of works by are illustrated by examples of computer analysis of the literary texts by O. Pamuk and Y. Kemal - two of Turkey's most prominent novelists. The hierarchical cluster analysis based on the occurrence of numerals in the texts by Pamuk and Kemal shows the author, genre, and chronology differences of numerals usage in the literary texts of these authors. © The Authors, published by EDP Sciences, 2021.
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85108383931
PURE ID: 22104525
ISSN: 25550403
DOI: 10.1051/e3sconf/202127001038
metadata.dc.description.sponsorship: We believe that the methodology we are developing can be a useful addition to the traditional stylometric practices of taking into account the length of sentences and words, the frequency of use of service words and certain significant parts of speech, etc. This work was supported by a grant from the Russian Foundation for Basic Research, project No. 19-012-00199A, “A New Method of Text Attribution Based on Statistics of Numerals”. This work was partially supported by a scholarship from the Slovak Academic Information Agency.
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