  Adoption of cultural innovation (e.g., music, beliefs, language) is often
geographically correlated, with adopters largely residing within the boundaries
of relatively few well-studied, socially significant areas. These cultural
regions are often hypothesized to be the result of either (i) identity
performance driving the adoption of cultural innovation, or (ii) homophily in
the networks underlying diffusion. In this study, we show that demographic
identity and network topology are both required to model the diffusion of
innovation, as they play complementary roles in producing its spatial
properties. We develop an agent-based model of cultural adoption, and validate
geographic patterns of transmission in our model against a novel dataset of
innovative words that we identify from a 10% sample of Twitter. Using our
model, we are able to directly compare a combined network + identity model of
diffusion to simulated network-only and identity-only counterfactuals --
allowing us to test the separate and combined roles of network and identity.
While social scientists often treat either network or identity as the core
social structure in modeling culture change, we show that key geographic
properties of diffusion actually depend on both factors as each one influences
different mechanisms of diffusion. Specifically, the network principally drives
spread among urban counties via weak-tie diffusion, while identity plays a
disproportionate role in transmission among rural counties via strong-tie
diffusion. Diffusion between urban and rural areas, a key component in
innovation diffusing nationally, requires both network and identity. Our work
suggests that models must integrate both factors in order to understand and
reproduce the adoption of innovation.
