Spatial Evolution of Human Dialects

Abstract

The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wave-like spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy's Curve giving the relationship between geographical and linguistic distance, and a generalisation of the curve to account for the presence of a population centre. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.

Emergence of order in random languages

“…For example, protein structure is written in sequences of amino acids, a language of 20 different symbols. A large body of previous work has investigated the social aspect of linguistic systems, namely that different agents must find consensus regarding the meaning of symbols [2,3,4]. A complementary but necessary aspect of any linguistic system concerns the hidden structure within the sequences themselves, independent of communication.…”

Statistical physics of language maps in the USA

“…We note the close match, and also that clusters appear to have densely populated areas at their heart with boundaries lying in less densely populated areas. These features were predicted by the memory based surface tension models [20,21] upon which the current paper builds. .…”

“…The social network through which linguistic forms spread may therefore be viewed as quasi two-dimensional, provided we take a sufficiently coarse grained view of the system. This has geometrical implications for the conformity driven evolution of language; if the social network over which language evolves is two dimensional, then linguistic boundaries may be viewed as lines and by analogy with conformity driven physical systems, we would expect these to feel surface tension [20,21,24]. We also observe from Figure 6 that the distribution of connections is not isotropic: a disproportionate number of edges appear to run closer to the east-west direction than to north-south.…”

“…Modern computers and the creation of the internet have dramatically improved data collection and analysis [4][5][6][7][8][9][10][11][12], and social media has provided a new source of linguistic data [13]. Modelling linguistic evolution has also emerged as a sub-field of statistical physics where ideas and techniques employed to relate the macroscopic behaviour of physical systems to their microscopic components have been applied [14][15][16][17][18][19][20][21][22]. However, there is a need to develop mathematical models which provide a scientific understanding of how humanlevel processes [23] give rise to the observed geographical distributions and language dynamics.…”

Brownian dynamics for the vowel sounds of human language

“…Moreover, certain arrangements within vowel space are particularly common [12][13][14]. Vowel systems, like most elements of languages, evolve over time and may therefore be viewed as dynamical systems coupled to human social dynamics, and also to geography and social networks [15][16][17]. Cross-linguistic similarities suggest that their internal dynamics may play a particularly powerful role, and numerous models have been proposed [13,14,[18][19][20][21][22][23][24][25].…”