🤖 AI Summary
This study addresses the lack of a standardized approach to visualizing emotional states in existing information systems. Through a systematic user study, it investigates how discrete emotions and dimensional affect models map onto visual variables—including color, size, speed, shape, and animation. The work establishes, for the first time, empirical associations between affective labels and multidimensional visual encodings, revealing that color, size, and speed are significantly correlated with discrete emotions, while speed also exhibits a strong relationship with arousal. These findings provide an empirical foundation for developing universal guidelines for affective visualization and advance the standardization of emotion representation in visual interfaces.
📝 Abstract
The paper concerns affective information systems that represent and visualize human emotional states. The goal of the study was to find typical representations of discrete and dimensional emotion models in terms of color, size, speed, shape, and animation type. A total of 419 participants were asked about their preferences for emotion visualization. We found that color, speed, and size correlated with selected discrete emotion labels, while speed correlated with arousal in a dimensional model. This study is a first step towards defining a universal emotion representation for use in information systems.