论文标题
语言变化不是中立的空间证据
Spatial evidence that language change is not neutral
论文作者
论文摘要
遗传和语言进化的中性理论认为，变体的相对频率通过随机漂移而进化。中性进化仍然是语言变化的合理的无效模型。在本文中，我们通过考虑语言调查中观察到的地理模式来反对中性假设。我们将扬声器建模为嵌入空间中的Hopfield网络中的神经元，类似于经典的二维晶格模型之一的统计物理学模型。模型的通用类别取决于神经元的激活功能的形式，该神经元编码说话者的学习行为。我们将英语方言调查产生的地图视为我们网络的样本。最大似然分析以及对真实图和模拟地图之间空间自动相关的比较表明，这些地图更有可能属于符合性驱动的Ising类，其中接口是由表面张力而不是中性选民类驱动的，而不是中性选民类别，它们是由噪声驱动的。
The neutral theory of genetic and linguistic evolution holds that the relative frequencies of variants evolve by random drift. Neutral evolution remains a plausible null model of language change. In this paper we provide evidence against the neutral hypothesis by considering the geographical patterns observed in language surveys. We model speakers as neurons in a Hopfield network embedded in space, analogous to one of the classical two dimensional lattice models of statistical physics. The universality class of the model depends on the form of the activation function of the neurons, which encodes learning behaviour of speakers. We view maps generated by the Survey of English Dialects as samples from our network. Maximum likelihood analysis, and comparison of spatial auto-correlations between real and simulated maps, indicates that the maps are more likely to belong to the conformity-driven Ising class, where interfaces are driven by surface tension, rather than the neutral Voter class, where they are driven by noise.
