Detecting Fake and Genuine Facebook Users Using Gradient Boosted Trees and Interpretable Machine Learning

Fake Facebook accounts can be used to spread misinformation or invade privacy. Traditional methods of identifying fake accounts are time- consuming, inefficient, and unreliable. Black-box AI models can make biased or unfair decisions, further discrediting computing power. Create a system to accurately identify fake and real Facebook users. To identify fake accounts and reduce human intervention, the proposed system must be fast, precise, and extensible. The proposed system aims to objectively and fairly identify fake Facebook accounts, reducing the risk of malicious activity and improving user experience. The proposed system should use explainable AI (XAI) to increase trust in technology and ensure user security by providing transparency and interpretability in decision-making.