Inferring Network Structure from Cascades

Sushrut Ghonge; Dervis Can Vural

doi:10.1103/physreve.96.012319

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arXiv · 1611.04861

Inferring Network Structure from Cascades

Sushrut Ghonge·Dervis Can Vural

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Abstract

Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.

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Sushrut Ghonge, Dervis Can Vural. 2017-07-21. Inferring Network Structure from Cascades. https://doi.org/10.1103/physreve.96.012319

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