Network Exchange Patterns in Online Communities Forthcoming in Organization Science

Large-scale online communities rely on computer-mediated communication between participants, enabling them to sustain interactions and exchange on a scale hitherto unknown. Yet, little research has focused on how these online communities sustain themselves and how their interactions are structured. In this paper, we theorize and empirically measure the network exchange patterns of long-duration sustainable online communities. We propose that participation dynamics follow specific forms of social exchange: direct reciprocity, indirect reciprocity, and preferential attachment. We integrate diverse findings about individual participation motivations by identifying how individual behavior manifests in network-level structures of online communities. We studied five online communities over 27 months and analyzed 38,483 interactions using exponential random graph (p*) models and mixed-effects ANCOVA analysis. In a test of competing models, we find that network exchange patterns in online community communication networks are characterized by direct reciprocity and indirect reciprocity patterns and, surprisingly, a tendency away from preferential attachment. Our findings undermine previous explanations that online exchange follows a power law distribution based on people wanting to connect to " popular " others in online communities. Our work contributes to theories of new organizational forms by identifying network exchange patterns that regulate participation and sustain online communities.