Predicting language diversity with complex networks

Evolution and propagation of the world’s languages is a complex phenomenon, driven, to a
large extent, by social interactions. Multilingual society can be seen as a system of interacting
agents, where the interaction leads to a modification of the language spoken by the individuals. Two people can reach the state of full linguistic compatibility due to the positive interactions,
like transfer of loanwords. But, on the other hand, if they speak entirely different languages,
they will separate from each other. These simple observations make the network science the
most suitable framework to describe and analyze dynamics of language change. Although many
mechanisms have been explained, we lack a qualitative description of the scaling behavior for
different sizes of a population. Here we address the issue of the language diversity in societies
of different sizes, and we show that local interactions are crucial to capture characteristics of
the empirical data. We propose a model of social interactions, extending the idea from, that
explains the growth of the language diversity with the size of a population of country or society.
We argue that high clustering and network disintegration are the most important characteristics
of models properly describing empirical data.
We analyze the model of social interactions with coevolution of the topology and states of the
nodes. This model can be interpreted as a model of language change. We propose different
rewiring mechanisms and perform numerical simulations for each. Obtained results are compared
with the empirical data gathered from two online databases and anthropological study
of Solomon Islands. We study the behavior of the number of languages for different system sizes
and we find that only local rewiring, i.e. triadic closure, is capable of reproducing results for
the empirical data in a qualitative manner. Furthermore, we cancel the contradiction between
previous models and the Solomon Islands case. Our results demonstrate the importance of the
topology of the network, and the rewiring mechanism in the process of language change.