Language Evolution and Computation Bibliography

Sociolinguistic studies have demonstrated that centrally-connected and peripheral members of social networks can both propel and impede the spread of linguistic innovations. We use agent-based computer simulations to investigate the dynamic properties of these network roles in a large social influence network, in which diffusion is modeled as the probabilistic uptake of one of several competing variants by agents of unequal social standing. We find that highly-connected agents, structural equivalents of leaders in empirical studies, advance on-going change by spreading competing variants. Isolated agents, or loners, holding on to existing variants are safe-keepers of variants considered old or new depending on the current state of the rest of the population. Innovations spread following a variety of S-curves and stabilize as norms in the network only if two conditions are simultaneously satisfied: (1) the network comprises extremely highly connected and very isolated agents, and (2) agents are biased to pay proportionally more attention to better connected, or popular, neighbors. These findings reconcile competing models of individual network roles in the selection and propagation process of language change, and support Bloomfield's hypothesis that the spread of linguistic innovations in heterogeneous social networks depend upon communication density and relative prestige.