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<p>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.</p>

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Modeling roles and trade-offs in multiplex networks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月7日

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  • Nikolaos Nakis,
  • Sune Lehmann,
  • Nicholas A. Christakis,
  • Morten Mørup

摘要

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.