  Some social networks, such as LinkedIn and ResearchGate, allow user
endorsements for specific skills. In this way, for each skill we get a directed
graph where the nodes correspond to users' profiles and the arcs represent
endorsement relations. From the number and quality of the endorsements
received, an authority score can be assigned to each profile. In this paper we
propose an authority score computation method that takes into account the
relations existing among different skills. Our method is based on enriching the
information contained in the digraph of endorsements corresponding to a
specific skill, and then applying a ranking method admitting weighted digraphs,
such as PageRank. We describe the method, and test it on a synthetic network of
1493 nodes, fitted with endorsements.
