A Dual Approach to Establishing the Authority of Technical Natural Language Texts and Their Components

V. I. Shynkarenko; I. M. Demidovich; O. S. Kuropiatnyk

doi:10.15802/stp2023/288958

Authors

V. I. Shynkarenko Ukrainian State University of Science and Technologies, Ukraine https://orcid.org/0000-0001-8738-7225
I. M. Demidovich Ukrainian State University of Science and Technologies, Ukraine https://orcid.org/0000-0002-3644-184X
O. S. Kuropiatnyk Ukrainian State University of Science and Technologies, Ukraine https://orcid.org/0000-0003-2286-884X

DOI:

https://doi.org/10.15802/stp2023/288958

Keywords:

graphs, formal grammars, constructivism, constructive-productive modeling, correlation coefficient, classification, statistical analysis, authorship determination, natural language texts

Abstract

Purpose. The study is aimed at testing the hypothesis that it is possible to determine plagiarism by methods of establishing the authorship of a text without using a text bank and their direct comparison. Methodology. Constructive and productive models of the processes of establishing the authorship of technical texts for two methods have been developed. The first method is based on the formation of a text model in the form of a set of formal substitution rules with probabilistic weights (as in stochastic formal grammars), which reflects the syntactic features and patterns of text formation by the author. The degree of similarity between the text under study and another text is determined by comparing their models. The second method is a classical approach to detecting borrowings (plagiarism) by directly comparing the text under study with an existing text bank, highlighting repeated text fragments, and determining the degree of originality. Experiments were conducted to establish the correlation between the results of these two methods. The experimental base consisted of 509 text sections of theses of students majoring in «Software Engineering». Findings. Experimental studies have made it possible to establish a high correlation between the results of the two methods. Correlation coefficients in the range of 0.75...1.0 and with an average value of 0.88 were obtained provided that borrowings are taken into account for text fragments of at least five words in length. Originality. For the first time, the authors have identified the possibilities and proposed methods for indirect plagiarism detection without using a large text bank. The essence of the model is to formalize the representation of the author's sentence syntax by a set of substitution rules with probabilistic weights. Practical value. Based on the results obtained, the possibilities for detecting borrowings have been expanded and the effectiveness of the corresponding methods has been increased. Recommendations on the parameters of classical methods for detecting borrowings have been obtained, in particular, it is recommended to take into account text fragments of at least five words in length as a rational parameter when using borrowing detection systems. The possibilities of text authorship detection methods tested on fiction texts are extended to technical texts.

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