Social Bot Detection

Social bot detection aims to identify automated accounts on social media platforms that spread misinformation and manipulate public opinion. Current research focuses on developing robust and adaptable detection methods, employing diverse approaches such as graph neural networks (GNNs) to leverage social network structures, random forests and contrastive learning techniques to improve classification accuracy, and adversarial training to enhance model resilience against sophisticated bots. These advancements are crucial for mitigating the harmful effects of online manipulation and improving the trustworthiness of information shared on social media platforms.