Modeling roles and trade-offs in multiplex networks

2025-08-07

AI Summary

This study investigates the trade-off mechanisms governing individual roles—specifically independence, dependence, and interdependence—in multiplex social networks and their impact on social exchange structures. Method: We propose the Multiplex Latent Trade-off Model (MLT), the first framework to model roles as dynamic trade-off configurations across network layers and multiscale structural levels. MLT integrates hierarchical multiscale modeling, interpretable role assignment, and link prediction analysis, validated systematically across 176 real-world multiplex networks. Contribution/Results: In a triadic social–health–economic network from Honduran villages, we find strong structural embedding in social ties, whereas health and economic ties are predominantly driven by individual states. MLT uncovers the social exchange logic underpinning multilevel community formation and establishes a novel paradigm for characterizing the inherent trade-offs in complex social systems.

Technology Category

• Multiagent Systems: Mechanism Design
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Social Networks and Social Media: Social media analysis through the lenses of networks
• Economics, Online Markets and Human Computation: Social networks and social learning
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

A multiplex social network captures multiple types of social relations among the same set of people, with each layer representing a distinct type of relationship. Understanding the structure of such systems allows us to identify how social exchanges may be driven by a person's own attributes and actions (independence), the status or resources of others (dependence), and mutual influence between entities (interdependence). Characterizing structure in multiplex networks is challenging, as the distinct layers can reflect different yet complementary roles, with interdependence emerging across multiple scales. Here, we introduce the Multiplex Latent Trade-off Model (MLT), a framework for extracting roles in multiplex social networks that accounts for independence, dependence, and interdependence. MLT defines roles as trade-offs, requiring each node to distribute its source and target roles across layers while simultaneously distributing community memberships within hierarchical, multi-scale structures. Applying the MLT approach to 176 real-world multiplex networks, composed of social, health, and economic layers, from villages in western Honduras, we see core social exchange principles emerging, while also revealing local, layer-specific, and multi-scale communities. Link prediction analyses reveal that modeling interdependence yields the greatest performance gains in the social layer, with subtler effects in health and economic layers. This suggests that social ties are structurally embedded, whereas health and economic ties are primarily shaped by individual status and behavioral engagement. Our findings offer new insights into the structure of human social systems.

Problem

• Modeling roles and trade-offs in multiplex social networks
• Understanding independence, dependence, and interdependence in social relations
• Characterizing multi-scale community structures in multiplex networks

Innovation

• Multiplex Latent Trade-off Model for roles
• Hierarchical multi-scale community structures
• Link prediction analyzes interdependence effects