Exploring language relations through syntactic distances and geographic proximity

Abstract

Languages are grouped into families that share common linguistic traits. While this approach has been successful in understanding genetic relations between diverse languages, more analyses are needed to accurately quantify their relatedness, especially in less studied linguistic levels such as syntax. Here, we explore linguistic distances using series of parts of speech (POS) extracted from the Universal Dependencies dataset. Within an information-theoretic framework, we show that employing POS trigrams maximizes the possibility of capturing syntactic variations while being at the same time compatible with the amount of available data. Linguistic connections are then established by assessing pairwise distances based on the POS distributions. Intriguingly, our analysis reveals definite clusters that correspond to well known language families and groups, with exceptions explained by distinct morphological typologies. Furthermore, we obtain a significant correlation between language similarity and geographic distance, which underscores the influence of spatial proximity on language kinships.

39 pages

References in corpus (9)

• Measuring and testing dependence by correlation of distances
• Entropy and information in neural spike trains: Progress on the sampling problem
• Indo-European languages tree by Levenshtein distance
• Interlinguistic similarity and language death dynamics
• On the origin of long-range correlations in texts
• Global-scale phylogenetic linguistic inference from lexical resources
• Dialectometric analysis of language variation in Twitter
• Global Syntactic Variation in Seven Languages: Towards a Computational Dialectology
• Entropy estimators for Markovian sequences: A comparative analysis