Title: Predicting language diversity with complex network,
Abstract: 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. 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.