Beyond Detection: Investing in Practical and Theoretical Applications of Emotion + Visualization

Emotion is a dynamic variable that modulates how we perceive, reason about, and interact with our environment. Recent studies have established that emotion’s influence carries to data analysis and visualization, impacting performance in ways both positive and negative. While we are still in the infancy of understanding the role emotion plays in analytical contexts, advances in physiological sensing and emotion research have raised the possibility of creating emotion-aware systems. In this position paper, we argue that it is critical to consider the potential advances that can be made even in the face of imperfect sensing, while we continue to address the practical challenges of monitoring emotion in the wild. To underscore the importance of this line of inquiry, we highlight several key challenges related to detection, adaptation, and impact of emotional states for users of data visualization systems, and motivate promising avenues for future research in these areas