Emotional Response

Emotional response research aims to understand how individuals experience and express emotions, focusing on both the subjective experience and observable manifestations. Current research utilizes diverse methods, including analyzing textual data with natural language processing models like T5 and LLMs, employing facial emotion recognition and physiological sensors, and developing machine learning models to classify emotions from various data sources (e.g., images, videos, interviews). This work has implications for improving human-computer interaction, aiding mental health assessment and intervention, and enhancing our understanding of how language and sensory experiences shape emotional responses.