With the success of online social networks and microblogging platforms such as Facebook, Flickr and Twitter, the phenomenon of influence-driven propagations, has recently attracted the interest of computer scientists, information technologists, and marketing specialists.

In this talk we take a data mining perspective and we discuss what (and how) can be learned from a social network and a database of traces of past propagations over the social network. Starting from one of the key problems in this area, i.e.  the identification of influential users, by targeting whom certain desirable marketing outcomes can be achieved, we provide an overview of some recent progresses in this area and discuss some open problems.