In this paper, we present a framework for automatic selection and composition of services which exploits trustworthiness of services as a metric for measuring the quality of service composition. Trustworthiness is defined in terms of service reputation extracted from user profiles. The profiles are, in particular, extracted and inferred from a social network which accumulates users past experience with corresponding services. Using our privacy inference model we, first, prune social network to hide privacy sensitive contents and, then, utilize a trust inference based algorithm to measure reputation score of each individual service, and subsequently trustworthiness of their composition.