Why do people think liberals drink lattes? How social media afforded self-presentation can shape subjective social sorting

TL;DR

This study investigates how social media self-presentation influences subjective social sorting, revealing that online profiles can reinforce political alignments and affect perceptions of polarization.

Contribution

It uniquely analyzes naturally occurring public identifiers on social media, showing how they contribute to social sorting and political polarization.

Findings

Most identifiers bridge political divides but some reinforce sorting

Social media profiles reflect and reinforce existing political alignments

Online identifiers can reveal both expected and unexpected relationships

Abstract

Social sorting, the alignment of social identities, affiliations, and/or preferences with partisan groups, can increase in-party attachment and decrease out-party tolerance. We propose that self-presentation afforded by social media profiles fosters subjective social sorting by shaping perceptions of alignments between non-political and political identifiers. Unlike previous work, we evaluate social sorting of naturally occurring, public-facing identifiers in social media profiles selected using a bottom-up approach. Using a sample of 50 million X users collected five times between 2016 and 2018, we identify users who define themselves politically and generate networks representing simultaneous co-occurrence of identifiers in profiles. We then systematically measure the alignment of non-political identifiers along political dimensions, revealing alignments that reinforce existing associations, reveal unexpected relationships, and reflect online and offline events. We find that while most identifiers bridge political divides, social sorting of identifiers along political lines is occurring to some degree in X profiles. Our results have implications for understanding the role of social media in facilitating (the perception of) polarization and polarization mitigation strategies such as bridging interventions and algorithms.