SWATTING Spambots: Real-time Detection of Malicious Bots on X

Spambot activity has become increasingly pervasive on social media platforms, such as X (formerly known as Twitter), leading to concerns over information quality and user experience. This study presents an innovative approach for real-time detection and reporting of spambots on Twitter platform. Using data analytics technique, we adapted a comprehensive framework capable of accurately identifying and categorizing spambot accounts based on their behavioral patterns and characteristics. By providing an efficient solution to this growing issue, our research aims to enhance user trust in social media communication channels and promote a more transparent and authentic online environment for users to engage with each other and share information.