Abstract
We define a model for the evolution of linguistic convention in a population of agents embedded on a network, and consider the effects of topology on the population-level language dynamics. Individuals are subject to evolutionary forces that over time result in the adoption of a shared language throughout the population. The differences in convergence time to a common language and that language’s communicative efficiency under different underlying social structures and population sizes are examined. We find that shorter average path lengths contribute to a faster convergence and that the final payoff of languages is unaffected by the underlying topology. Compared to models for the emergence of linguistic convention based on self-organization, we find similarities in the effects of average path lengths, but differences in the role of degree heterogeneity. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.