The patterns of musical inuence on the Last.Fm social network

One classic problem definition in social network analysis is the study of diffusion in networks, which enables us to tackle problems like favoring the adoption of positive technologies. Most of the attention has been turned to how to maximize the number of influenced nodes, but this approach misses the fact that different scenarios imply different diffusion dynamics, only slightly related to maximizing the number of nodes involved. In this paper we study the patterns of musical influenced through a social network. First, we define a procedure to extract musical leaders, i.e. users who start the diffusion of new music albums through the social network. Second, we measure three different dimensions of musical influenced: The Width, i.e. the ratio of neighbors influenced by a leader; the Depth, i.e. the degrees of separation from a leader to its influenced nodes; and the Strength, i.e. the intensity of the influenced from a leader. We validate our results on a social network extracted from the Last.Fm music platform.