Exploring the Need to Use “Plagiarism” Detection Software Rationally

Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism,...

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Main Authors: Petar Milovanovic, Tatjana Pekmezovic, Marija Djuric
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Publications
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Online Access:https://www.mdpi.com/2304-6775/13/1/1
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author Petar Milovanovic
Tatjana Pekmezovic
Marija Djuric
author_facet Petar Milovanovic
Tatjana Pekmezovic
Marija Djuric
author_sort Petar Milovanovic
collection DOAJ
description Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university and journal staff, for various reasons, often erroneously interpret the degree of plagiarism based on the percentage of textual overlap shown in the similarity report. This is often accompanied by explicit recommendations to the author(s) to paraphrase the text to achieve an “acceptable” percentage of overlap. Here, based on the available literature and real-world examples from similarity reports, we provide a classification with extensive examples of phrases that falsely inflate the similarity index and argue the futility and dangers of rephrasing such statements just for the sake of reducing the similarity index. The examples provided in this paper call for a more reasonable assessment of text similarity. To fully endorse the principles of academic integrity and prevent loss of clarity of the scientific literature, we believe it is important to shift from pure bureaucratic and quantificational view on the originality of scientific texts to human-centered qualitative assessment of the manuscripts, including the software outputs.
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spelling doaj-art-005a5eceb9c54db8a631113ab408482d2025-08-20T03:43:55ZengMDPI AGPublications2304-67752025-01-01131110.3390/publications13010001Exploring the Need to Use “Plagiarism” Detection Software RationallyPetar Milovanovic0Tatjana Pekmezovic1Marija Djuric2Center of Bone Biology, Institute of Anatomy, Faculty of Medicine, University of Belgrade, 11000 Belgrade, SerbiaInstitute of Epidemiology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, SerbiaCenter of Bone Biology, Institute of Anatomy, Faculty of Medicine, University of Belgrade, 11000 Belgrade, SerbiaUniversities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university and journal staff, for various reasons, often erroneously interpret the degree of plagiarism based on the percentage of textual overlap shown in the similarity report. This is often accompanied by explicit recommendations to the author(s) to paraphrase the text to achieve an “acceptable” percentage of overlap. Here, based on the available literature and real-world examples from similarity reports, we provide a classification with extensive examples of phrases that falsely inflate the similarity index and argue the futility and dangers of rephrasing such statements just for the sake of reducing the similarity index. The examples provided in this paper call for a more reasonable assessment of text similarity. To fully endorse the principles of academic integrity and prevent loss of clarity of the scientific literature, we believe it is important to shift from pure bureaucratic and quantificational view on the originality of scientific texts to human-centered qualitative assessment of the manuscripts, including the software outputs.https://www.mdpi.com/2304-6775/13/1/1text similarityplagiarism detection“tortured” phrasesparaphrasingassessment
spellingShingle Petar Milovanovic
Tatjana Pekmezovic
Marija Djuric
Exploring the Need to Use “Plagiarism” Detection Software Rationally
Publications
text similarity
plagiarism detection
“tortured” phrases
paraphrasing
assessment
title Exploring the Need to Use “Plagiarism” Detection Software Rationally
title_full Exploring the Need to Use “Plagiarism” Detection Software Rationally
title_fullStr Exploring the Need to Use “Plagiarism” Detection Software Rationally
title_full_unstemmed Exploring the Need to Use “Plagiarism” Detection Software Rationally
title_short Exploring the Need to Use “Plagiarism” Detection Software Rationally
title_sort exploring the need to use plagiarism detection software rationally
topic text similarity
plagiarism detection
“tortured” phrases
paraphrasing
assessment
url https://www.mdpi.com/2304-6775/13/1/1
work_keys_str_mv AT petarmilovanovic exploringtheneedtouseplagiarismdetectionsoftwarerationally
AT tatjanapekmezovic exploringtheneedtouseplagiarismdetectionsoftwarerationally
AT marijadjuric exploringtheneedtouseplagiarismdetectionsoftwarerationally