Artificial Intelligence and Machine Learning Algorithms for Assessing the Authenticity of a Scientific Article in Scopus: Translator's Experience

Abstract

Objective. This paper examines ways to solve the problem of cross-language plagiarism in scientific works written in Ukrainian, which are to be translated and published in English. Considering that Ukrainian university libraries are directly involved in the practices of improving the level of awareness of lecturers and scientists, as well as their support of a large number of new digital tools, we draw attention to the emergence of new opportunities in the practices of supporting academic integrity. Methods. Big Data mining techniques and analysis of algorithms underlying machine translation software were employed to identify the cases of cross-language plagiarism in scientific articles originally written in the Ukrainian language. Results. Based on the analysis of 4000 translated manuscripts, it was established that the standard Microsoft Word 2022 software, typically used to write an article, identifies with a very high accuracy those parts of the text that had been earlier published and stored in a digital format. Conclusions. With the advent of Microsoft Office 365 software (released in 2022), it becomes possible to check any article originally written in Ukrainian or Russian, while being translated into English, for similarities with previously published academic papers. This allows for an instantaneous correction check that may prove useful in preventing the intended or unintended occurrence of cross-language plagiarism in scientific papers. It is advisable to more actively involve librarians of Ukrainian universities in using the powerful potential of digital support for the research activities of their users, including writing papers and checking them for signs of plagiarism.