The Complexity of Associative Diffusion: Reassessing the Relationship between Network Structure and Cultural Variation

Goldberg and Stein (2018) present an innovative agent-based computational model that shows how cultural associations can diffuse through superficial interpersonal interactions. They counterintuitively argue that segmented networks—for example, those resembling “small worlds” with dense local clustering—inhibit rather than promote cultural diffusion. This finding is notable because it breaks with a long line of influential research showing that local clustering is crucial to diffusion in cases where behaviors and practices—including cultural beliefs—require multiple reinforcements in order to spread. Replicating Goldberg and Stein’s model, we find this result only holds consistently in settings approximating small-group interactions. In models with larger populations, and where cultural associations require repeated reinforcement through social observation, locally clustered small-world networks can promote global cultural variation as well as globally-connected networks, and sometimes do so better. The complex interactions among parameters that lead to this reversal in Goldberg and Stein’s model are instructive for theoretical models of interpersonal influence.