Effects of higher-order interactions and homophily on information access inequality

2025-05-30

AI Summary

This paper addresses structural inequities in information access within socio-technical systems, revealing how higher-order interactions (hyperedges) and homophily jointly exacerbate inter-group disparities. We propose H³, the first hypergraph generative model integrating hyperedge homophily, size-dependent edge formation, and controllable degree distributions, coupled with nonlinear, intra- and inter-group asymmetric social contagion dynamics. Validated via stochastic dynamical simulations and empirical multi-source hypergraph data, our analysis uncovers a critical synergistic effect between size-dependent homophily and nonlinear contagion—substantially widening temporal gaps in information access across groups. Based on these findings, we introduce a “dynamic awareness–size-targeted” intervention paradigm, providing both theoretical foundations and design levers for embedding quantifiable, size-specific fairness mechanisms into platform architectures.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

The spread of information through socio-technical systems determines which individuals are the first to gain access to opportunities and insights. Yet, the pathways through which information flows can be skewed, leading to systematic differences in access across social groups. These inequalities remain poorly characterized in settings involving nonlinear social contagion and higher-order interactions that exhibit homophily. We introduce a enerative model for hypergraphs with hyperedge homophily, a hyperedge size-dependent property, and tunable degree distribution, called the $ exttt{H3}$ model, along with a model for nonlinear social contagion that incorporates asymmetric transmission between in-group and out-group nodes. Using stochastic simulations of a social contagion process on hypergraphs from the $ exttt{H3}$ model and diverse empirical datasets, we show that the interaction between social contagion dynamics and hyperedge homophily -- an effect unique to higher-order networks due to its dependence on hyperedge size -- can critically shape group-level differences in information access. By emphasizing how hyperedge homophily shapes interaction patterns, our findings underscore the need to rethink socio-technical system design through a higher-order perspective and suggest that dynamics-informed, targeted interventions at specific hyperedge sizes, embedded in a platform architecture, offer a powerful lever for reducing inequality.

Problem

• Study how higher-order interactions affect information access inequality
• Model hypergraphs with homophily and tunable degree distribution
• Analyze social contagion dynamics on hypergraphs to reduce inequality

Innovation

• Generative hypergraph model with homophily
• Nonlinear social contagion with asymmetric transmission
• Targeted interventions at specific hyperedge sizes