Understanding interpersonal relationships provides important context in understanding spoken communication. In addition to increasing knowledge of the social indicators in spoken communication, the automatic recognition of interpersonal relationships has an application in providing structure to social networks. This paper presents exploratory work on the challenging problem of distinguishing family from friends in spontaneous dialogs drawn from the CALLHOME English corpus. We find both acoustic/prosodic and lexical features useful in classifying these relationships. In binary classification experiments, we achieve accuracy of 10.71% absolute improvement over chance (50%) assignment.