Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America.
Department of Physics, Rensselaer Polytechnic Institute, Troy, New York, United States of America.
PLoS One. 2020 May 12;15(5):e0232888. doi: 10.1371/journal.pone.0232888. eCollection 2020.
Increasing evidence demonstrates that in many places language coexistence has become ubiquitous and essential for supporting language and cultural diversity and associated with its financial and economic benefits. The competitive evolution among multiple languages determines the evolution outcome, either coexistence, or decline, or extinction. Here, we extend the Abrams-Strogatz model of language competition to multiple languages and then validate it by analyzing the behavioral transitions of language usage over the recent several decades in Singapore and Hong Kong. In each case, we estimate from data the model parameters that measure each language utility for its speakers and the strength of two biases, the majority preference for their language, and the minority aversion to it. The values of these two biases decide which language is the fastest growing in the competition and what would be the stable state of the system. We also study the system convergence time to stable states and discover the existence of tipping points with multiple attractors. Moreover, the critical slowdown of convergence to the stable fractions of language users appears near and peaks at the tipping points, signaling when the system approaches them. Our analysis furthers our understanding of evolution of various languages and the role of tipping points in behavioral transitions. These insights may help to protect languages from extinction and retain the language and cultural diversity.
越来越多的证据表明,在许多地方,语言共存已经变得无处不在,对于支持语言和文化多样性及其相关的经济和金融利益至关重要。多种语言之间的竞争进化决定了进化的结果,是共存、衰退还是灭绝。在这里,我们将 Abrams-Strogatz 语言竞争模型扩展到多种语言,并通过分析新加坡和中国香港近几十年来语言使用行为的转变来验证它。在每种情况下,我们根据数据估计模型参数,这些参数衡量了每种语言对其使用者的效用,以及两种偏见的强度,即对其语言的多数偏好和对其语言的少数回避。这两个偏见的价值决定了哪种语言在竞争中增长最快,以及系统的稳定状态是什么。我们还研究了系统向稳定状态收敛的时间,并发现存在多个吸引子的临界点。此外,在接近和达到临界点时,语言使用者的稳定部分的收敛速度会出现明显的放缓并达到峰值,这表明系统正在接近它们。我们的分析进一步加深了我们对各种语言进化的理解,以及临界点在行为转变中的作用。这些见解可能有助于保护语言免受灭绝,并保留语言和文化多样性。