Bot Detector

Bot detection research focuses on identifying automated accounts (bots) across various online platforms, aiming to mitigate their harmful effects like misinformation spread and manipulation. Current efforts leverage machine learning, employing techniques like large language models, LSTM autoencoders, and ensemble methods to analyze diverse user data including textual content, behavioral patterns, and even keystroke dynamics. The field is grappling with challenges such as adversarial bot strategies designed to evade detection and the limitations of existing datasets, highlighting the need for more robust and generalizable models to ensure the integrity and safety of online environments.