The Role of Social Network Structure in the Emergence of Linguistic Structure.

Limor Raviv,Shiri Lev‐Ari,Antje Meyer

doi:10.1111/cogs.12876

Abstract

Social network structure has been argued to shape the structure of languages, as well as affect the spread of innovations and the formation of conventions in the community. Specifically, theoretical and computational models of language change predict that sparsely connected communities develop more systematic languages, while tightly knit communities can maintain high levels of linguistic complexity and variability. However, the role of social network structure in the cultural evolution of languages has never been tested experimentally. Here, we present results from a behavioral group communication study, in which we examined the formation of new languages created in the lab by micro-societies that varied in their network structure. We contrasted three types of social networks: fully connected, small-world, and scale-free. We examined the artificial languages created by these different networks with respect to their linguistic structure, communicative success, stability, and convergence. Results did not reveal any effect of network structure for any measure, with all languages becoming similarly more systematic, more accurate, more stable, and more shared over time. At the same time, small-world networks showed the greatest variation in their convergence, stabilization, and emerging structure patterns, indicating that network structure can influence the community's susceptibility to random linguistic changes (i.e., drift).

Highlights

Why are languages so different from each other? One possible explanation is that selective pressures associated with social dynamics and language use can influence the emergence and distribution of different linguistic properties—making language typology a mirror of the social environment (Lupyan & Dale, 2016)
We examined the formation of new languages that were developed by different micro-societies that varied in their network structure
We predicted that there would be more input variability in sparser networks, given that in such networks, some of the community members never directly interact. We hypothesized that this greater input variability and difficulty in convergence would induce a stronger pressure for generalization and systemization, which would result in the sparser networks creating more systematic languages compared to fully connected networks

Summary

Introduction

One possible explanation is that selective pressures associated with social dynamics and language use can influence the emergence and distribution of different linguistic properties—making language typology a mirror of the social environment (Lupyan & Dale, 2016). According to this hypothesis, often referred to as the Linguistic Niche Hypothesis, the structure of languages is shaped by the structure of the community in which they evolved. Exoteric communities tend to be much bigger and sparser societies, in which there is a higher degree of language contact and more interaction with strangers and, a higher proportion of non-native speakers

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