Experienced Emotion

Research on experienced emotion focuses on understanding and modeling how humans experience, express, and respond to emotions, bridging the gap between psychological and computational perspectives. Current research emphasizes developing and evaluating computational models, often employing deep learning architectures like transformers (e.g., BERT, GPT) and convolutional neural networks, to analyze emotional expression in text, images, audio, and physiological data. This work is significant for advancing our understanding of human emotion and has practical applications in areas such as mental health support, personalized AI assistants, and content moderation.