ENAI Working Group

Testing of Support Tools for Plagiarism Detection

There are a number of systems available for free or as a paid service, some are available online, some can be downloaded and used locally. Academics around the globe are naturally interested in the question – which of these systems is the best?

Members

  • Tomáš Foltýnek, Masaryk University, Czechia (head)
  • Alla Anohina-Naumeca, Riga Technical University, Latvia
  • Debora Weber-Wulff, HTW Berlin, Germany
  • Dita Henek Dlabolová, European Network for Academic Integrity, Czechia
  • Jean Gabriel Guerrero, University of Monterey, Mexico
  • Július Kravjar, European Network for Academic Integrity, Slovakia
  • Laima Kamzola, Riga Technical University, Latvia
  • Lorna Waddington, University of Leeds, United Kingdom
  • Olumide Popoola, Queen Mary University of London, United Kingdom
  • Özgür Çelik, Balikesir University, Türkiye
  • Salim Razı, Canakkale Onsekiz Mart University, Türkiye
  • Sonja Bjelobaba, Uppsala University, Sweden
  • Tolga Özşen, Canakkale Onsekiz Mart University, Türkiye

Motivation

Plagiarism detection tools, also known as text-matching software, are expected to use the state-of-the-art methods to detect plagiarism. Expected output is the suspicious document, where plagiarized parts are highlighted (showing WHAT was copied), together with links to potential sources (showing WHERE these parts come from. To reveal HOW the source was changed, human consideration is needed.

The most methodologically sound comparison used to be done by prof. Debora Weber-Wulff and her team. In their last test in 2013, 15 tools were compared. The selection of the tools was done based on previous comparisons. The researchers used set of documents mostly in English and German.

Since then, there has not been any systematic and methodologically sound testing of support tools for plagiarism detection since 2013.

Goal

European Network for Academic Integrity decided to fill this gap and prepared a new methodology of testing including brand new dataset containing documents from multiple European languages plagiarized from various sources and obfuscated by various methods.

Outputs and Materials

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