A master's thesis at the College of Computer Science and Information Technology, University of Basrah, was titled "Detecting Automated Accounts on the X Platform (Twitter) Using Supervised Machine Learning."

The thesis, presented by student Zahraa Imad Hassan, aimed to develop an intelligent framework for detecting automated accounts by integrating static and temporal characteristics and employing machine learning and deep learning algorithms.

The thesis concluded that integrating temporal and static characteristics contributes to improving detection accuracy, and that the Stacking Ensemble model achieved the best results compared to other models, thus enhancing the efficiency of detecting automated accounts on social media platforms.