The structure of online social networks modulates the rate of lexical change

TL;DR

This study analyzes how the structure of online social networks influences the introduction, persistence, and diversity of new words over a decade, revealing that network properties significantly affect lexical change.

Contribution

It provides large-scale empirical evidence that online community network structures impact lexical innovation and retention, highlighting differences from offline communities.

Findings

Dense connections hinder lexical change

External contacts promote lexical innovation

Online communities support niche words without leveling

Abstract

New words are regularly introduced to communities, yet not all of these words persist in a community's lexicon. Among the many factors contributing to lexical change, we focus on the understudied effect of social networks. We conduct a large-scale analysis of over 80k neologisms in 4420 online communities across a decade. Using Poisson regression and survival analysis, our study demonstrates that the community's network structure plays a significant role in lexical change. Apart from overall size, properties including dense connections, the lack of local clusters and more external contacts promote lexical innovation and retention. Unlike offline communities, these topic-based communities do not experience strong lexical levelling despite increased contact but accommodate more niche words. Our work provides support for the sociolinguistic hypothesis that lexical change is partially shaped by the structure of the underlying network but also uncovers findings specific to online communities.