This paper presents a novel approach to analyzing and grouping natural languages based on the degree of their chaoticity. It clusters 52 languages from 18 language families, according to the value of the entropy–complexity pair, to reveal the chaotic properties of semantic trajectories. The obtained clusters appear to be closely correlated with the family of languages under consideration as well as to certain language characteristics (word order, alignment, locus of marking, and morphological complexity). The study also proposes a robust method for assessing the chaoticity of a time series. The findings suggest the pressing need for a more in‐depth investigation of how particular linguistic features and chaotic aspects of language are interrelated.
Yerbolova et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: