Stylometry Analysis of Human and Machine Text for Academic Integrity

📝 Original Info

• Title: Stylometry Analysis of Human and Machine Text for Academic Integrity
• ArXiv ID: 2601.01225
• Date: 2026-01-03
• Authors: Hezam Albaqami, Muhammad Asif Ayub, Nasir Ahmad, Yaseen Ahmad, Mohammed M. Alqahtani, Abdullah M. Algamdi, Almoaid A. Owaidah, Kashif Ahmad

📝 Abstract

This work addresses critical challenges to academic integrity, including plagiarism, fabrication, and verification of authorship of educational content, by proposing a Natural Language Processing (NLP)-based framework for authenticating students' content through author attribution and style change detection. Despite some initial efforts, several aspects of the topic are yet to be explored. In

📄 Full Content

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