Exploring language relations through syntactic distances and geographic proximity
This work addresses the need for more accurate analyses of language relations, particularly in syntax, for linguists and researchers studying language evolution and typology, though it is incremental in applying existing methods to new data.
The authors tackled the problem of quantifying linguistic relatedness, especially at the syntactic level, by using parts-of-speech trigrams from the Universal Dependencies dataset to compute pairwise distances, revealing clusters that correspond to known language families and a significant correlation between language similarity and geographic distance.
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.