What is it about?
In the academic world, using paraphrasing tools to disguise plagiarized content is becoming a significant issue. Our study focuses on detecting such machine-paraphrased plagiarism. We tested various AI-driven methods to see how well they could identify text that had been altered by tools like SpinBot and SpinnerChief. We used preprints, theses, and Wikipedia articles for this purpose. Our top-performing AI model, Longformer, was able to detect paraphrased plagiarism with high accuracy, surpassing both existing software like Turnitin and human evaluators in effectiveness. This research provides a new tool for educators and publishers to maintain academic honesty by spotting sophisticated forms of plagiarism.
Featured Image
Photo by Towfiqu barbhuiya on Unsplash
Read the Original
This page is a summary of: Identifying Machine-Paraphrased Plagiarism, January 2022, Springer Science + Business Media,
DOI: 10.1007/978-3-030-96957-8_34.
You can read the full text:
Contributors
The following have contributed to this page
