Inferring network structure from cascades
Sushrut Ghonge1,2, Dervis Can Vural2
1Department of Physics, Indian Institute of Technology Delhi, Delhi 110016, India.
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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