Intersectional inequalities in social networks

TL;DR

This paper investigates how multidimensional connection preferences and attribute correlations in social networks influence inequalities, revealing complex patterns and providing analytical models validated by real-world data.

Contribution

It introduces a novel network model that captures intersectional inequalities and analytically predicts their emergence, validated with high school friendship data.

Findings

Attribute correlation amplifies inequalities in multidimensional networks.

Model predictions align closely with real-world social network data.

Counterintuitive inequality patterns emerge from biased multidimensional preferences.

Abstract

Social networks are shaped by complex, intersecting identities that drive our connection preferences. These preferences weave networks where certain groups hold privileged positions, while others become marginalized. While previous research has examined the impact of single-dimensional identities on inequalities of social capital, social disparities accumulate nonlinearly, further harming individuals at the intersection of multiple disadvantaged groups. However, how multidimensional connection preferences affect network dynamics and in what forms they amplify or attenuate inequalities remains unclear. In this work, we systematically analyze the impact of multidimensionality on social capital inequalities through the lens of intersectionality. To this end, we operationalize several notions of intersectional inequality in networks. Using a network model, we reveal how attribute correlation (or consolidation) combined with biased multidimensional preferences lead to the emergence of counterintuitive patterns of inequality that are unobservable in one-dimensional systems. We calibrate the model with real-world high school friendship data and derive analytical closed-form expressions for the predicted inequalities, finding that the model's predictions match the observed data with remarkable accuracy. These findings hold significant implications for addressing social disparities and inform strategies for creating more equitable networks.