Networks and identity drive the spatial diffusion of linguistic innovation in urban and rural areas

Cultural innovation is often regionally adopted, commonly attributed to either demographic identity signaling or diffusion through homophilous networks. This study shows that network and identity play complementary roles in determining where new language is adopted, requiring models to incorporate both. The authors develop an agent-based model of cultural adoption and validate geographic properties against a dataset of innovative words identified from a 10% Twitter sample. By comparing a combined network+identity model to network-only and identity-only counterfactuals, they find that network principally drives spread among urban counties via weak-tie diffusion, identity disproportionately drives transmission among rural counties via strong-tie diffusion, and diffusion between urban and rural areas requires both factors. Models must integrate both network and identity to understand and reproduce adoption of innovation.

Aparna Ananthasubramaniam, David Jurgens, Daniel M. Romero