Online Behavior

Online behavior research focuses on understanding and modeling how individuals interact in digital environments, aiming to detect and characterize coordinated actions, predict user engagement, and identify malicious activities like cyberbullying and the spread of misinformation. Current research employs diverse methods, including machine learning algorithms (e.g., SVMs, convolutional neural networks), natural language processing techniques, and novel approaches like transforming behavioral sequences into images for analysis. These studies have significant implications for improving online safety, enhancing digital platform design, and informing the development of ethical and responsible AI systems.