Determining the Authorship of a Ukrainian-Language Literary Text by Means of Artificial Intelligence from Ultra-Short Excerpts

Author:

Ivanov O. P.1ORCID,Shynkarenko V. I.1ORCID,Skalozub V. V.1ORCID,Kosolapov A. A.1ORCID

Affiliation:

1. Ukrainian State University of Science and Technologies, Ukraine

Abstract

Purpose. The intelligent search engine Bing can be used as a method and a means of determining the author of a Ukrainian-language test. Bing helps to find information about a text fragment and its author, but the search results may be inaccurate or incomplete. The main purpose of the paper is to study the effectiveness of establishing the authorship of literary texts by state-of-the-art artificial intelligence tools based on ultra-short excerpts. Methodology. Ten Ukrainian authors with a rich body of fiction reflecting various aspects of Ukrainian culture and history were selected, as well as random fragments of 3–7 words each from different works of these authors. An experiment was conducted to determine the authorship of 2,000 fragments. Findings. Using the Python programming language and the skpy package, we developed software that sends questions and receives answers from the Bing bot built into Microsoft Skype. The answers were checked for the name of the author of the phrase and the corresponding title of the work. According to the results, Ivan Franko has the highest percentage of answers where the author's name was mentioned (65%), and Oleksandr Dovzhenko has the lowest result (23%). The answers were analyzed by the length of the fragments. Of course, the longer the length of a text fragment, the greater the likelihood of accurately identifying its authorship. Features of the author's style are manifested in 20–40 % of short fragments. The remaining 60–80% may be commonly used language constructions that the author relayed from the external environment. Originality. In this work, for the first time, the method of checking the authorship of fragments of Ukrainian-language text using the Bing bot with artificial intelligence is presented. A comparative analysis was performed and experiments were given to determine the authorship of short fragments of 3–7 words. It has been established that even quite small fragments of the text have signs characteristic of the original style of the author of artistic works. Practical value. It has been determined to what extent experts in determining the authorship of natural language texts can rely on existing state-of-the-art artificial intelligence tools in combination with an extensive database of texts in the Internet space.

Publisher

Ukrainian State University of Science and Technologies

Subject

General Engineering

Reference11 articles.

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3. Bonifacic, I. (2023). Microsoft’s next-gen Bing uses a ‘much more powerful’ language model than ChatGPT. Retrieved from https://www.engadget.com/microsofts-next-gen-bing-more-powerful-language-model-than-chatgpt-182647588.html (in English)

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