Inferring Network Structure from Cascades.

Authors: 
Ghonge, S., and Vural D.C
Citation: 
Physical Review E, 96.1 (2017): 012319
Publication Date: 
July, 2017

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.