This paper proposes Habit, an efficient multi-layered approach to content dissemination in Delay Tolerant Networks (DTN) that leverages information about nodes' colocation (physical layer) and their social network (application layer). More precisely, the regularity of users' colocation is learned based on historical colocation observations; also, the users' social network (or `network of interest') is dynamically propagated during periods of colocation; finally, these distinct pieces of information are locally combined and used to compute the paths that content should follow, in a way that maximises both precision (i.e., nodes receive only content they are interested in) and recall (i.e., all relevant content is received by interested nodes).