Learning thresholds lead to stable language coexistence.

IF 2.2 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS
M V Tamm, E Heinsalu, S Scialla, M Patriarca
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引用次数: 0

Abstract

We introduce a language competition model that is based on the Abrams-Strogatz model and incorporates the effects of memory and learning in the dynamics of language shift. On a coarse-grained timescale, the effects of memory and learning can be expressed as thresholds on the speakers' fractions of the competing languages. In its simplest form, the resulting model is exactly solvable. Besides the consensus on one of the two languages, the model describes additional equilibrium states that are not present in the Abrams-Strogatz model: a stable dynamical coexistence of the two languages and a frozen state coinciding with the initial state. We show numerically that these results are preserved for threshold functions of a more general shape. The comparison of the model predictions with historical datasets demonstrates that while the Abrams-Strogatz model fails to describe some relevant language competition situations, the proposed model provides a good fitting.

学习门槛导致语言的稳定共存。
我们介绍了一个基于艾布拉姆斯-斯特罗加茨模型的语言竞争模型,该模型将记忆和学习的影响纳入语言迁移的动态中。在粗粒度的时间尺度上,记忆和学习的影响可以用说话者在竞争语言中的分数的阈值来表示。在最简单的形式下,得到的模型是完全可解的。除了对两种语言中的一种达成共识之外,该模型还描述了在艾布拉姆斯-斯特罗加茨模型中不存在的额外平衡状态:两种语言的稳定动态共存和与初始状态一致的冻结状态。我们在数值上表明,这些结果对于更一般形状的阈值函数是保留的。模型预测与历史数据集的比较表明,虽然艾布拉姆斯-斯特罗加茨模型未能描述一些相关的语言竞争情况,但所提出的模型提供了良好的拟合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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