In this paper we present <b>MORE</b> (acronym of <i><b>MORE</b> than <b>MO</b>vie <b>RE</b>commendation</i>), a Facebook application that semantically recommends movies to the user leveraging the knowledge within Linked Data and the information elicited from her profile. <b>MORE</b> exploits the power of social knowledge bases (e.g. DBpedia) to detect semantic similarities among movies. These similarities are computed by a Semantic version of the classical Vector Space Model (sVSM), applied to semantic datasets. <b>MORE</b> is freely available as a Facebook application.