Crowd-science: How Leaders’ Emotions Shape Online Participation

Abstract

To resolve complex scientific challenges, scientists increasingly collaborate with online communities. However, maintaining a high level of participation in crowd-science projects is difficult. This research aims to understand how leaders’ expressions of emotions can enhance voluntary participation in crowd-science projects. This research is based on Polymath, a crowd-science project where professional and non-professional mathematicians collaborate to solve very difficult problems. Drawing on Emotion As a Social Information (EASI) Theory, we explore the influence of leaders’ emotions on subsequent participation with a multi-level count analysis. We find that (1) leaders’ positive emotions have a positive relationship through participants’ positive emotions with participation’s quantity and quality, and (2) leaders’ negative emotions have a negative relationship through participants’ cognitive complexity. By examining the role of leaders’ affective dimension in crowd-science projects, our research brings theoretical contributions to crowd science and online community leadership literatures. Our research also extends the EASI theory through the exploration of its mechanisms, through its application in text-based communication contexts and highlights the importance of emotional intensity. Limits and future directions are discussed.