Abstract—Social networks can be used to model social interactions between individuals. In many circumstances, not all interactions between individuals are observed. In such cases, a social network is constructed with the data that has been observed, as this is the best one can do. Recent research has attempted to predict future links in a social network, though this has proven a very challenging task. Rather than predicting future links, we propose an inference method for recovering the links in a social network that already exist but that have not been observed. In addition, our approach automatically identifies groups of individuals that form tight-knit communities and models the intra and inter-community interactions. At this evel of abstraction and for a social network built from mobile phone calls, our method is able to accurately identify a subset of 10% of all community pairs where about 50% of the pairs have had unobserved communication between them, an improvement of about ...