Tutorials across different categories in a longform format & with interactive elements
How to identify machine-paraphrased plagiarism
Employing paraphrasing tools to conceal plagiarized text is a severe threat to academic integrity. To enable the detection of machine-paraphrased text, we evaluate the effectiveness of five pre-trained word embedding models combined with machine learning classifiers and state-of-the-art neural language models. We analyze preprints of research papers, graduation theses, and Wikipedia articles, which we paraphrased using different configurations of the tools SpinBot and SpinnerChief and show that the automated classification alleviates shortcomings of widely-used text-matching systems, such as Turnitin and PlagScan.