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Mitigating cascades in coevolving networks with targeted rewiring.

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Summary

This study introduces superspreader nodes to control adoption cascades in networks. Targeted rewiring by these nodes reduces costs and network changes, enhancing system efficiency and stability.

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Area of Science:

  • Network science
  • Sociophysics
  • Complex systems

Background:

  • Understanding how network structure influences opinion dynamics is crucial.
  • Previous models often lack efficiency in managing adoption cascades and network adaptation.

Purpose of the Study:

  • To investigate the coevolution of network structure and opinion dynamics.
  • To introduce a novel targeted rewiring mechanism involving superspreader nodes.

Main Methods:

  • Integration of a threshold-based complex contagion model with targeted rewiring.
  • Mean-field theoretical analysis.
  • Numerical simulations.

Main Results:

  • Targeted rewiring by superspreader nodes efficiently contains adoption cascades.
  • Significantly reduces the number of rewiring operations required.
  • Localizes structural adaptation to critical network points, ensuring economical and stable evolution.

Conclusions:

  • The superspreader mechanism offers a more efficient and realistic approach to network intervention.
  • Substantially reduces intervention costs and rewiring burden with minimal structural change.