The paper outlines an agent-based model for language choice in multilingual communities and tests its performance on samples of data drawn from a large-scale sociolinguistic survey carried out in Estonia. While previous research in the field of language competition has focused on diachronic applications, utilizing rather abstract models of uniform speakers, we aim to model synchronic language competition among more realistic, data-based agents. We hypothesized that a reasonably parametrized simulation of interactions between agents endowed with interaction principles grounded in sociolinguistic research would give rise to a network structure resembling real-world social networks, and that the distribution of languages used in the model would resemble their actual usage distribution. The simulation was reasonably successful in replicating the real-world scenarios, while further analysis revealed that the model parameters differ in importance between samples. We conclude that such variation should be considered in parametrizing future language choice and competition models.

本文概述了一种基于代理的多语言社区中的语言选择模型，并根据在爱沙尼亚进行的大规模社会语言学调查得出的数据样本测试了其性能。尽管先前在语言竞争领域的研究集中在历时性应用上，利用统一的演讲者的相当抽象的模型，但我们的目标是在更现实的，基于数据的代理中对共时语言竞争进行建模。我们假设，基于社会语言学研究而赋予交互作用原理的行为者之间的交互进行合理的参数化仿真，将形成类似于现实世界社交网络的网络结构，并且模型中使用的语言分布将类似于其实际用法分布。该模拟在复制真实场景中相当成功，而进一步的分析表明，样本之间模型参数的重要性不同。我们得出结论，在参数化将来的语言选择和竞争模型时应考虑这种变化。