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Information spreading on multiplex networks is complex. Switching costs between online and offline layers affect spread dynamics non-monotonically, revealing crucial insights for realistic social network modeling.

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Area of Science:

  • Complex Systems
  • Network Science
  • Information Dynamics

Background:

  • Multiplex networks feature multiple interaction layers (e.g., online, offline).
  • Information spreading models often simplify network structures.
  • Layer-switching costs introduce complexity in cross-layer transmissions.

Purpose of the Study:

  • To model information spreading on multiplex networks with layer-switching costs.
  • To analyze the impact of multiplexity and path-dependent transmissibility on spreading dynamics.
  • To investigate the influence of network layer densities and seed infection types on epidemic thresholds and prevalence.

Main Methods:

  • Formulation of an analytical framework for path-dependent transmissibility.
  • Development of a model for information spreading on multiplex networks.
  • Analysis of epidemic thresholds and prevalence under varying layer-switching costs.

Main Results:

  • Epidemic threshold and prevalence exhibit non-monotonic responses to layer-switching costs.
  • Optimal spreading conditions can change abruptly and non-analytically.
  • Multiplexity significantly influences spreading dynamics, with layer densities and seed types playing key roles.

Conclusions:

  • Explicit consideration of multiplexity is crucial for accurate modeling of information spreading.
  • Layer-switching costs create complex, non-intuitive dynamics in multiplex networks.
  • Findings are essential for predicting phenomena on diverse, modern social interaction networks.