We address a problem of predicting diffusion probabilities in complex networks. As one approach to this problem, we focus
on the independent cascade (IC) model, and define the likelihood for information diffusion episodes, where an episode means
a sequence of newly active nodes. Then, we present a method for predicting diffusion probabilities by using the EM algorithm.
Our experiments using a real network data set show the proposed method works well.