We present a study of the relationship between music genres and graph-related metrics in a directed graph of music credits built using data from Spotify. Our objective is to examine crediting patterns and their dependence on music genre and artist popularity. To this end, we introduce a node-wise index of reciprocity, which could be a useful feature in recommendation systems. We argue that reciprocity allows distinguishing between the two types of connections: citations and collaborations. Previous works analyse only undirected graphs of credits, making the assumption that every credit implies a collaboration. However, this discards all information about reciprocity. To avoid this oversimplification, we define a directed graph. We show that, as previously found, the most central artists in the network are classical and hip-hop artists. Then, we analyse the reciprocity of artists to demonstrate that the high centrality of the two groups is the result of two different phenomena. Classical artists have low reciprocity and most of their connections are attributable to citations, while hip-hop artists have high reciprocity and most of their connections are true collaborations.