figure2b,c(3).nb from Quantifying the spatial pattern of dialect words spreading from a central population

Some dialect words are shared among geographically distant groups of people without close interaction. Such a pattern may indicate the current or past presence of a cultural centre exerting a strong influence on peripheries. For example, concentric distributions of dialect variants in Japan may be explicable by repeated inventions of new variants at Kyoto, the ancient capital, with subsequent outward diffusion. Here we develop a model of linguistic diffusion within a population network to quantify the distribution of variants created at the central population. Equilibrium distributions of word ages are obtained for idealized networks and for a realistic network of Japanese prefectures. Our model successfully replicates the observed pattern, supporting the notion that a centre–periphery social structure underlies the emergence of concentric patterns. Unlike what has previously been claimed, our model indicates that a novelty bias in linguistic transmission is not always necessary to account for the concentric pattern, whereas some bias in the direction of transmission between populations is needed to be consistent with the observed absence of old words near the central population. Our analysis on the realistic network also suggests that the process of linguistic transmission was not much affected by between-prefecture differences in population size.

地理上相距遥远且无密切互动的人群之间，会共享部分方言词汇（dialect words）。这类分布模式或可表明，历史上或当下存在一个对边缘区域施加强影响力的文化中心（cultural centre）。例如，日本境内的方言变体同心分布（concentric distributions）现象，便可通过古都京都（Kyoto）的背景得到解释：新方言变体持续在京都诞生，随后向外扩散。本研究构建了人口网络内的语言扩散（linguistic diffusion）模型，以量化起源于核心人口群体的方言变体的分布特征。我们分别在理想化网络与真实的日本都道府县（Japanese prefectures）人口网络中，推导出了词汇年代（word ages）的均衡分布（equilibrium distributions）。本模型成功复现了观测到的分布模式，印证了"同心模式的形成根植于中心-边缘社会结构（centre–periphery social structure）"这一学术观点。与此前的研究论断不同，本模型表明，语言传递（linguistic transmission）中的新颖性偏差（novelty bias）并非解释同心分布模式的必要条件；但为契合"核心区域附近缺乏古老词汇"这一观测结果，群体间的传递方向偏差仍是不可或缺的。此外，针对真实人口网络的分析还显示，语言传递过程并未受到都道府县间人口规模差异的显著影响。