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Backbone reconstruction in temporal networks from epidemic data.

Francesco Vincenzo Surano1,2, Christian Bongiorno1,3, Lorenzo Zino2

  • 1Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy.

Physical Review. E
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Summary
This summary is machine-generated.

This study introduces a new algorithm to identify strong ties in complex systems using node dynamics during a spreading process. This method aids in developing targeted immunization strategies by pinpointing influential nodes.

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Area of Science:

  • Network Science
  • Complex Systems Analysis
  • Dynamical Processes

Background:

  • Complex systems exhibit time-varying interactions, including strong ties (dyadic) and weak ties (attribute-based).
  • Understanding the interplay between strong and weak ties is crucial for dynamical processes.
  • Accurate, time-varying interaction topology data is often unavailable, making tie distinction challenging.

Purpose of the Study:

  • To develop a statistically-principled algorithm for reconstructing the backbone of strong ties from node dynamics during a spreading process.
  • To validate the algorithm's performance on diverse synthetic datasets.
  • To integrate the algorithm into a targeted immunization strategy.

Main Methods:

  • An algorithm was developed based on analytical results to infer strong ties from time-series data of node states during a spreading process.
  • Numerical validation was performed using various synthetic datasets.
  • Monte Carlo simulations and a real-world case study were employed to test the immunization strategy.

Main Results:

  • The proposed algorithm successfully reconstructs the backbone of strong ties.
  • The method was validated across synthetic datasets with features mirroring real-world systems.
  • Integration into a targeted immunization strategy proved viable, prioritizing influential nodes.

Conclusions:

  • The developed algorithm offers a statistically sound method for inferring strong ties from node dynamics.
  • This approach facilitates effective targeted immunization strategies in complex systems.
  • The study demonstrates the practical applicability of the algorithm in real-world scenarios.