Fake Profile Social Media Detection Using ANN Model
Keywords:
Advanced deep learning techniques, Analysis of user interactions, Artificial Neural Network (ANN) applications, Dataset preprocessing techniques, Detection of fake profiles, Enhanced online safety, Identification of fraudulent accounts, Innovative machine learning strategies, Optimized feature extraction, Secure social media platformsAbstract
The rise of social media platforms has brought along challenges, such as creating and misusing fake profiles, leading to issues like online fraud, misinformation, and identity theft. This project introduces a system for detecting fake social media profiles using an Artificial Neural Network (ANN) model. The model evaluates user data, including profile details, account creation history, interaction trends, and activity patterns, to identify anomalies indicative of fake accounts. Through supervised learning, the ANN is trained on a comprehensive dataset comprising both authentic and fraudulent profiles, enabling it to identify hidden patterns and deliver precise predictions. The system is designed to adapt to evolving behaviors and ensure scalability across multiple platforms. By automating fake profile detection, this research improves the security and trustworthiness of social media environments.
