Unmasking deceptive profiles: A deep dive into fake account detection on instagram and twitter

¹ College of Pharmacy, University of Al-Ameed, Karbala PO Box 198, Iraq
² College of Health and Medical Techniques, University of Alkafeel, Al-Najaf, Iraq
³ College of Medicine, University of Al-Ameed, Karbala PO Box 198, Iraq
⁴ College of Dentistry, University of Al-Ameed, Karbala PO Box 198, Iraq

^* Corresponding Author: salam.sehen@qu.edu.iq

Abstract

The rise of online social networks, also known as OSNs, has captured the attention of younger generations and made them an integral part of social life. As a result, the use of various social media platforms has increased significantly, greatly impacting individuals' social connections. These platforms offer a wide range of features, such as news distribution, contributing to their widespread use. However, with the rapid growth of social media, the prevalence of fake accounts has become a major problem, posing a threat to both the security of users and the integrity of these platforms. In response, this article explores the effectiveness of machine learning algorithms (ML). Detect and identify fraudulent accounts on popular social media platforms, especially Instagram and Twitter. Our methodology involves analyzing user activity and account information to develop fine-tuned machine-learning models. Our approach takes into account important parameters such as number of followers, number of posts, and engagement.