Affect Infusion and Detection through Faces in Computer-mediated Knowledge-sharing Decisions

Abstract

Faces are important in both human communication and computer-mediated communication. In this study, I analyze the influence of emotional expressions in faces on knowledge-sharing decisions in a computer-mediated environment. I suggest that faces can be used for affect infusion and affect detection, which increases the effectiveness of knowledge-management systems. Using the affect infusion model, I discuss why emotions can be expected to influence knowledge-sharing decisions. Using the two-step primitive emotional contagion framework, I found that emotional facial expression attached to a knowledge-sharing request influenced knowledge-sharing decisions. This influence was mediated by the decision maker’s emotional valence in the facial expression tracked by Face Reader technology and held for females but not males. I discuss implications for designers of emotionally intelligent information systems and research.