The Similarity Index of Scientific Publications with Mathematical Equations and Formulas

Abstract

The problems of estimating the similarity index of mathematical and other scientific publications containing equations and formulas are discussed for the first time. The presence of equations and formulas significantly complicates the study of such texts. The possibilities of the most popular anti-plagiarism software, the iThenticate system, currently used in scientific journals, are investigated for detecting plagiarism and self-plagiarism. The results of processing by this system of specific test problems containing many equations and formulas are presented. It was found that the iThenticate system often significantly overestimates the similarity index and therefore cannot distinguish between self-plagiarism and pseudo-self-plagiarism (false self-plagiarism). This article will be valuable to researchers and university teachers in mathematics, physics, and engineering sciences, software programmers, as well as a wide range of readers interested in issues of plagiarism and self-plagiarism.