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Fake Profile Detection on social media Using Python
Online social networks represent one of the largest digital ecosystems, with more than 4 billion users worldwide. With this rapid expansion, the risk of maintaining data integrity and security has significantly increased. Social media platforms face numerous security challenges, as users often provide limited personal information, making identity verification difficult. This creates opportunities for scammers to generate fake accounts and misuse them to steal sensitive information, spread misinformation, or harm other users. As a result, detecting fake profiles in social networks has become a complex and important task. This project utilizes various machine learning and deep learning techniques applied to different datasets to identify the most effective model for detection. Additionally, a web-based system is developed to determine whether a given user profile is real or fake. The system is designed with four modules representing major social media platforms that are rapidly gaining users. Each module contains a trained model specifically developed for detecting fake profiles on that platform. Currently, the system has been implemented for Instagram, enabling accurate identification of fake profiles through the developed model with improved performance.
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