Antisocial Behavior

Antisocial behavior, encompassing online harassment, toxic communication, and the spread of misinformation, is a growing concern across various platforms and contexts. Current research focuses on detecting and mitigating this behavior using machine learning models, including graph neural networks and LSTM-CNN architectures, to analyze social media data and identify patterns indicative of antisocial tendencies. Understanding the dynamics of antisocial behavior, particularly its spread across online communities and the impact of platform policies like banning, is crucial for developing effective strategies to foster safer and more civil online environments. This research has implications for improving online safety, promoting responsible technology design, and informing public policy regarding online interactions.