Lexical diversity as a lens into the classification of Slavic languages: A quantitative typology perspective.

This article focuses on a data-driven linguistic classification method using lexical diversity metrics derived from a large-scale multilingual parallel corpus to classify Slavic languages while controlling for covariates like text genre and semantic content. By modeling type–token relationships and calculating three lexical diversity measures—Shannon's H, Yule's K, and type–token ratio (TTR)—the study demonstrates that these metrics effectively reflect the continuum of morphological complexity from analytism to synthetism and correspond closely to the established genealogical classification of Slavic languages. Hierarchical clustering based on combined lexical diversity metrics achieved 100% accuracy in grouping Slavic languages into their East, West, and South branches, and the geographical distribution of lexical diversity showed a monotonic increase from southwest to northeast within the Slavic-speaking region, consistent with prior global findings. The study advocates for the use of parallel corpora and quantitative typology as reliable, theory-independent tools for language classification and typological research.