Convergence Versus Divergence: How Exposure to Unfamiliar Colleagues Within and Across Network Communities Affects Social Belonging and Network Change

Social belonging is a fundamental human need, which people experience to varying degrees in the workplace. Interventions to boost belonging have typically focused on changing individuals’ mindsets. We instead develop a structural intervention that seeks to foster belonging by exposing people to unfamiliar colleagues—ones they are not in regular contact with. We consider two forms of such exposure: convergent, to colleagues from the same network community as the focal actor; and divergent, to colleagues from different network communities. Participants in a non-profit organization (N=213) engaged in a facilitated professional development program with unfamiliar colleagues and were randomly assigned to either convergent or divergent groups. Consistent with pre-registered expectations, convergent-condition participants reported more group solidarity and—three months post-intervention—more persistent ties to fellow group members and greater social belonging. Using computational linguistics and machine learning techniques to impute survey responses, we further show that convergent-condition participants experienced greater belonging than did a synthetic control group. Yet, pointing to the tradeoffs of the two forms of exposure, divergent-exposure participants experienced steeper declines in network constraint and greater increases in betweenness and closeness centrality, independent of fellow-group-member ties. We discuss implications for research on social networks, workplace belonging, and organizational interventions.