Leveraging percolation theory to single out influential spreaders in networks

@article{Radicchi2016LeveragingPT,
  title={Leveraging percolation theory to single out influential spreaders in networks},
  author={Filippo Radicchi and Claudio Castellano},
  journal={Physical review. E},
  year={2016},
  volume={93 6},
  pages={
          062314
        }
}
Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of… 

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