Detecting ghostwriters in high schools

Magnus Stavngaard, August Sørensen, Stephan Lorenzen*, Niklas Hjuler, Stephen Alstrup

*Corresponding author for this work
1 Citation (Scopus)

Abstract

Students hiring ghostwriters to write their assignments is an increasing problem in educational institutions all over the world, with companies selling these services as a product. In this work, we develop automatic techniques with special focus on detecting such ghostwriting in high school assignments. This is done by training deep neural networks on an unprecedented large amount of data supplied by the Danish company MaCom, which covers 90% of Danish high schools. We achieve an accuracy of 0.875 and a AUC score of 0.947 on an evenly split data set.

Original languageEnglish
Title of host publicationESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Number of pages6
PublisherESANN (i6doc.com)
Publication date2019
Pages197-202
ISBN (Electronic)9782875870650
Publication statusPublished - 2019
Event27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019 - Bruges, Belgium
Duration: 24 Apr 201926 Apr 2019

Conference

Conference27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019
Country/TerritoryBelgium
CityBruges
Period24/04/201926/04/2019
SeriesESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

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