From Categorical to Dimensional: A Multifaceted Approach to Emotions

Abstract

Current emotion research utilizes two primary frameworks: categorical and dimensional. Each framework offers unique insight, but also faces challenges in capturing the full spectrum of emotional experience. This study compares and integrates categorical and dimensional approaches to better understand their applications and limitations in emotion research, particularly in enhancing human-centered designs. Using Plutchik’s Wheel and the Self-Assessment Manikin (SAM), 238 participants rated their emotional responses to AI- generated images of various driving scenarios. Subsequently, the categories of emotions were mapped into the valence and arousal space. The integration of categorical and dimensional models revealed significant variability in individual interpretations of different emotions, highlighting the complexity and non-uniformity of emotional experience. These findings suggest that emotions may require more than two dimensions for full representation. A multifaceted approach that combines both frameworks can offer a comprehensive understanding of emotions and is essential for developing effective, empathetic, human-centered applications.