Languages show substantial variability between their speakers, but it is currently unclear how the structure of the communicative network contributes to the patterning of this variability. While previous studies have highlighted the role of network structure in language change, the specific aspects of network structure that shape language variability remain largely unknown. To address this gap, we developed a Bayesian agent‐based model of language evolution, contrasting between two distinct scenarios: language change and language emergence. By isolating the relative effects of (...) specific global network metrics across thousands of simulations, we show that global characteristics of network structure play a critical role in shaping interindividual variation in language, while intraindividual variation is relatively unaffected. We effectively challenge the long‐held belief that size and density are the main network structural factors influencing language variation, and show that path length and clustering coefficient are the main factors driving interindividual variation. In particular, we show that variation is more likely to occur in populations where individuals are not well‐connected to each other. Additionally, variation is more likely to emerge in populations that are structured in small communities. Our study provides potentially important insights into the theoretical mechanisms underlying language variation. (shrink)

Relationships between phonological and morphological complexity have long been proposed in the linguistic literature, with empirical investigations often seeking complexity trade-offs. Positive complexity correlations tend not to be viewed in terms of motivations. We argue that positive complexity correlations can be diachronically well-motivated, emerging from crosslinguistically prevalent processes of language change. We examine the correlation between syllable complexity and morphological synthesis, hypothesizing that the process of grammaticalization motivates a positive relationship between the two features. To test this, we conduct a (...) typological survey of 95 diverse languages and a corpus study of 21 languages with substantive corpora from the DoReCo project. The first study establishes a significant positive correlation between syllable complexity, measured in terms of maximal syllable patterns, and the index of synthesis. The second study tests the hypothesis that the relationship between syllable complexity and synthesis holds at local levels and within noun and verb types, as predicted by a grammaticalization account. While the findings of the corpus study are limited in their statistical power, the observed tendencies are consistent with our predictions. This study contributes important findings to the complexity literature, as well as a novel method which incorporates broad typological sampling and deep corpus analysis. (shrink)