Uncovering Social Network Structures through Penetration Data

We propose a method for uncovering the structure of the adopters' network underlying the diffusion process, based on penetration data alone. By uncovering the traces that this network leaves on the dissemination process, the degree distribution of the network can be estimated. We show that the network's degree distribution has a significant effect on the contagion properties. Ignoring the network structure introduces significant errors to estimated diffusion parameters and may lead to flawed assessments of the magnitude of the contagion process. In three studies we validate the proposed method using data for known mapped networks and the adoption process propagating on them.