A Guide to Higher-Order Homophily
2026-06-01 • Social and Information Networks
Social and Information Networks
AI summaryⓘ
The authors explain how people often interact more with those who are like them (homophily) or more with those who are different (heterophily). They focus on these patterns in hypergraphs, which capture group interactions instead of just pairs. The paper reviews ways to measure these patterns in hypergraphs and shows how they differ from traditional pair-based approaches. They also summarize models that describe how these mixing patterns happen in complex social systems. This work helps others choose the right methods to study social connections beyond just pairs of people.
homophilyheterophilyhypergraphssocial networksmixing patternshigher-order interactionsnetwork modelspairwise measures
Authors
Moritz Laber, Brennan Klein
Abstract
Homophily, the overrepresentation of interactions among similar individuals, and heterophily, the elevated prevalence of interactions among dissimilar ones, are frequently observed mixing patterns in social networks. As hypergraphs are increasingly used to represent social systems, a higher-order perspective on homophily and heterophily becomes ever more relevant. Here, we provide two complementary perspectives on this problem: First, we survey measures that can be used to quantify homophily (or heterophily) in hypergraphs -- emphasizing conceptual differences to existing pairwise measures -- and explain each measure through in-depth examples. Second, we provide an overview of hypergraph models for higher-order mixing patterns, distinguishing several model families with distinct use cases. By providing a guide to existing methods and synthesizing the current body of knowledge on higher-order homophily and heterophily, we lay the basis for informed methodological choices and future developments.