TL;DR
This paper presents a minimal network growth model for human language, incorporating node addition, edge rewiring, and link creation, to explain observed properties of syntactical word webs.
Contribution
It introduces a new, simplified network model that captures key features of syntactical word webs, advancing understanding of language as a complex network.
Findings
The model reproduces measured data of syntactical word webs.
It demonstrates the importance of node addition and rewiring in language networks.
The approach offers a minimal yet effective explanation of language network properties.
Abstract
The phenomenon of human language is widely studied from various points of view. It is interesting not only for social scientists, antropologists or philosophers, but also for those, interesting in the network dynamics. In several recent papers word web, or language as a graph has been investigated. In this paper I revise recent studies of syntactical word web. I present a model of growing network in which such processes as node addition, edge rewiring and new link creation are taken into account. I argue, that this model is a satisfactory minimal model explaining measured data.
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