Emotion Theory

Emotion theory research aims to understand how emotions are formed, experienced, and expressed, focusing on bridging the gap between subjective experience and observable behaviors. Current research employs various computational models, including probabilistic generative models like multilayered multimodal latent Dirichlet allocation and ontology-based frameworks, to analyze emotion from multimodal data (vision, physiology, language) and predict emotional responses based on events and appraisals. This work has implications for improving human-computer interaction, particularly in robotics and affective computing, as well as advancing our understanding of the cognitive and neural mechanisms underlying emotion.