The Similarity Index of Scientific Publications with Mathematical Equations and Formulas

Andrei D. Polyanin, Inna K. Shingareva*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
JournalPublishing Research Quarterly
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • iThenticate system
  • Mathematical and physical sciences
  • Self-plagiarism
  • Similarity index
  • Texts with equations and formulas

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