We investigate the diffusion of linguistic innovations on a fully connected network to understand the emergence of linguistic diversity. We employ an agent-based dynamics based on the Axelrod model, where interactions between agents are driven by homophily and social influence, with the difference that we assume that all agents share a number of common features that ensure a finite probability of pairwise interaction. We start from a homogeneous population and introduce zealots that act like agents spreading linguistic innovations, without being influenced by other agents. We analyze how different factors, such as the degree of cohesion and number of zealots in different linguistic states, determine the linguistic configurations that populations can adopt and contribute to the possible emergence of a multilinguistic community. The results are compared with those derived within the mean-field approximation.

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• Animal behavior, social interactions & emergent phenomena
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• Social system dynamics
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• Dynamical systems
• Language models
• Social dynamics