ANN Based Fake Profile Detection and Categorization Using Premetric Paradigms On Instagram
Afifa Salsabil Fathima, Syeda Reema, Syed Thouheed Ahmed · 2023
This study, focused on the behavioral analysis for the identification of social media accounts, endeavors to discern counterfeit profiles within social media networks by employing machine learning methodologies. The investigation is underpinned by a comprehensive dataset encompassing various user behavior-related attributes, including but not limited to the count of followers, followings, posts, private account status, and other relevant factors. The data is subjected to rigorous preprocessing procedures, which involve feature scaling and the division of the dataset into distinct training and testing subsets. Subsequently, a neural network model is trained utilizing the training dataset and rigorously evaluated using performance metrics such as accuracy and loss on the testing dataset. Additionally, the study delves into an examination of the confusion matrix to provide insight into the classification performance and offers a visual representation of the distribution of genuine and counterfeit accounts. The experimental results substantiate the model's efficacy in successfully identifying fake accounts through an in-depth analysis of their behavioral patterns.