Suspicious Commenter

"Suspicious commenter" research focuses on automatically identifying unusual or malicious online behavior, aiming to improve detection of various harmful activities. Current research employs diverse methods, including machine learning models like CNNs, LSTMs, and graph-based approaches, analyzing textual data, video streams, and network interactions to detect patterns indicative of suspicious activity such as fake news propagation, wildlife trafficking, stalking, or exam cheating. These advancements have significant implications for enhancing online safety, combating crime, and maintaining the integrity of online platforms and processes.