SPAMMER DETECTION AND FAKE USER IDENTIFICATION ON SOCIAL NETWORKS

This paper proposes a detection method for fake and clone profiles on Twitter. Clone profiles are detected using two methods: the C4.5 decision tree algorithm and Similarity Measures (evaluating attributes and network relationships). A comparison of these methods shows their effectiveness in detecting clone profiles. Online Social Networks (OSNs) face growing security and privacy concerns, especially with fake and clone profiles—fake profiles are created for malicious activities, while clone profiles replicate legitimate user information to harm the original owner’s identity and launch threats like phishing or spamming.