Collaborative Filtering Recommender Systems are one of the most used and well-known tools in the e-commerce area because they are adaptive and they do not need information about the recommended items. Although many studies have been proposed to take advantage of the information gathered by this kind of recommender systems, none have focused on the use of social network analysis. In this contribution we present a first approach that shows some of the advantages and results that can be obtained applying this methodology.