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March 10, 2026Nature Communications2 citationsOpen Access

Modeling roles and trade-offs in multiplex networks

NNNikolaos NakisSLSune LehmannNCNicholas A. Christakis

Key Points

  • The research aims to understand roles and trade-offs in multiplex social networks through a new modeling framework.
  • Introduced the Multiplex Latent Trade-off Model (MLT) for modeling roles.
  • Applied MLT to analyze 176 multiplex networks from villages in western Honduras.
  • Examined social, health, and economic layers to identify core social exchange principles.
  • Conducted link-prediction analyses to assess the impact of various attributes on tie predictions.
  • Identified key principles of social exchange within multiplex networks.
  • Found that interdependence improves predictions for social ties more than other factors.
  • Observed that health and economic ties are influenced primarily by individual status and behavior.

Abstract

Multiplex social networks capture multiple types of relations among the same people. Their structure reflects how exchanges arise from individual attributes related to independence, the status or resources of others related to dependence, and mutual influence related to interdependence. Understanding these systems is challenging because layers can play distinct yet complementary roles. We introduce the Multiplex Latent Trade-off Model, MLT, a framework for identifying roles in multiplex networks that incorporates independence, dependence, and interdependence. MLT represents roles as trade-offs, requiring each node to distribute source and target roles across layers while allocating community memberships within hierarchical structures. Applying MLT to 176 multiplex networks, including social, health, and economic layers from villages in western Honduras, we identify core principles of social exchange and reveal multi-scale communities. Link-prediction analyses show that modeling interdependence most improves predictions for social ties, whereas health and economic ties are shaped more strongly by individual status and behavior.

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Cite This Study

Nakis et al. (2026) studied this question.

synapsesocial.com/papers/69af947370916d39fea4b7cahttps://doi.org/10.1038/s41467-026-68896-1
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