Acquiring expected influence curve from single diffusion sequence

Abstract

We address the problem of estimating the expected influence curves with good accuracy from a single observed information diffusion sequence, for both the asynchronous independent cascade (AsIC) model and the asynchronous linear threshold (AsLT) model. We solve this problem by first learning the model parameters and then estimating the influence curve using the learned model. Since the length of the observed diffusion sequence may vary from a very long one to a very short one, we evaluate the proposed method by simulation using artificial diffusion sequence of various lengths and show that the proposed method can estimate the expected influence curve robustly from a single diffusion sequence with various lengths. © 2010 Springer-Verlag Berlin Heidelberg.