Language bubbles in online social networks

TL;DR

This paper investigates how social network fragmentation in Italian Twitter communities correlates with linguistic differences, revealing that isolated groups tend to have less diverse and poorer language use, forming 'language bubbles'.

Contribution

It introduces the concept of 'language bubbles' by linking social network structure with linguistic diversity and richness in online communities.

Findings

Communities closer in the network share more vocabulary.

Isolated communities show lower lexical diversity.

Social fragmentation correlates with linguistic divergence.

Abstract

Social media platforms have become essential spaces for public discourse. While political polarisation and limited communication across different groups are widely acknowledged, the connection between social network fragmentation and the language features and quality used by various communities has received insufficient attention. This study aims to fill this gap by examining the social structure and linguistic richness of the Italian debate on Twitter/X. We analyse tweets and retweets from Italian politicians and news outlets between 2018 and 2022, characterising the retweet network and evaluating the language used within different communities through various lexical metrics. Our analysis uncovers two systematic patterns: communities closer in the network tend to use more similar vocabulary, while isolated communities consistently demonstrate lower lexical diversity and richness. Together, these patterns illustrate what we call ``language bubbles''. These findings indicate that socially isolated communities interact less with others and develop distinct and poorer linguistic profiles, highlighting a structural link between social fragmentation and linguistic divergence.