Community interactions at crowd scale: hybrid crowds on the GitHub platform

Abstract

Communities and crowds have both been popular settings for the study of open innovation, but until recently, scholars have tended to study each in relative isolation from the other. The separate study of communities and crowds may mask commonalities and areas of overlap. In this exploratory study, we examine hybrid crowds, which exhibit norms of reciprocity common in communities, as well as patterns of contribution dispersion common in crowds. We show empirical variation along these two dimensions using data from six machine learning projects hosted on the GitHub software platform. We discuss the implications of hybrid crowds for sponsoring firms and opportunities for further research by scholars of open innovation.