Gonçalves Bruno, Sánchez David
Aix-Marseille Université, CNRS, CPT, UMR 7332, 13288 Marseille, France; Université de Toulon, CNRS, CPT, UMR 7332, 83957 La Garde, France.
Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (UIB-CSIC), E-07122 Palma de Mallorca, Spain.
PLoS One. 2014 Nov 19;9(11):e112074. doi: 10.1371/journal.pone.0112074. eCollection 2014.
We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.
我们使用带有地理标签的微博数据集对语言的地域差异进行了大规模分析。通过收集两年多来用西班牙语撰写的所有推特消息,我们构建了一个语料库,从该语料库中精心挑选的一系列概念使我们能够在全球范围内描述西班牙语的变体。聚类分析证明存在具有共同词汇属性的明确宏观区域。值得注意的是,我们发现西班牙语分为两种超级方言,一种是在美国和西班牙主要城市使用的城市方言,另一种是涵盖农村地区和小镇的多样化形式。后者可以进一步聚类为具有更强地域特征的较小变体。