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Optimal network modularity for information diffusion.

Azadeh Nematzadeh1, Emilio Ferrara1, Alessandro Flammini1

  • 1School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.

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|September 6, 2014
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Summary
This summary is machine-generated.

Strong communities can surprisingly boost information spread. Optimal network modularity, balancing local and global spread, minimizes the initial adopters needed for widespread diffusion.

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Area of Science:

  • Network Science
  • Information Diffusion Models

Background:

  • Understanding information diffusion is crucial in complex networks.
  • Community structure significantly influences network dynamics.

Purpose of the Study:

  • To investigate how community structure affects information diffusion.
  • To analyze the role of social reinforcement in this process.

Main Methods:

  • Utilizing the linear threshold model for information diffusion simulation.
  • Employing both analytical approaches and numerical simulations.
  • Examining networks with varying degrees of modularity.

Main Results:

  • Modular network structures can have counterintuitive impacts on diffusion.
  • Strong communities can enhance local spreading, facilitating global diffusion.
  • An optimal level of network modularity exists for efficient diffusion.

Conclusions:

  • Network modularity plays a critical role in information diffusion dynamics.
  • Social reinforcement can alter the effects of community structure.
  • Identifying optimal modularity can minimize the seed set for widespread information adoption.