Language dynamics within adaptive networks: An agent-based approach of nodes and links coevolution

TL;DR

This paper models language competition in adaptive networks where agents can rewire their interactions based on language preferences, revealing how community size influences language extinction or segregation.

Contribution

It introduces a local rewiring mechanism in network models of language competition, capturing agents' adaptive behavior and its effects on language dynamics.

Findings

Small networks tend to form linguistically segregated communities.

Large networks are more likely to experience language extinction.

Minority speaker fraction increases with total population size.

Abstract

Motivated by the dramatic disappearance of endangered languages observed in recent years, a great deal of attention has been given to the modeling of language competition in order to understand the factors that promote the disappearance of a language and its unfolding dynamics. With this in mind, we build on existing network models of language competition in bilingual societies. These models deal with the interplay between the usage of a language (link state) and the preference or attitude of the speakers towards the language (node state). In this work, we allow for the case where agents have the freedom to adapt their local interactions in accordance with their language preference. This is modeled by introducing a local rewiring mechanism triggered by the dissatisfaction of an agent with its usage of a given language. Our numerical simulations show that permitting this freedom to agents likely results in linguistically segregated communities for small network sizes. However, for networks of sufficiently large size, the extinction of one of the languages is the most probable scenario. Furthermore, we analyze how the fraction of minority speakers changes with the system size and we find that this fraction grows as the total population increases, which is consistent with existing data. Overall, the results of this work help us understand the impact of speakers' preferences and choices in the complex language landscape of bilingual societies.