@article{Colaiori_PhysRevE, author = { Francesca Colaiori and Claudio Castellano and Christine F. Cuskley and Vittorio Loreto and Martina Pugliese and Francesca Tria},journal = {PhysicalReview E},note = {language},pages = {012808},publisher = {American Physical Society},title = {General three-state model with biased population replacement: Analytical solution and application to language dynamics},type = {article},volume = {91},year = {2015},url = {http://link.aps.org/doi/10.1103/PhysRevE.91.012808},abstract = {

Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularise irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behaviour may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviours in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behaviour. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.

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