Link Me Baby One More Time: Social Music Discovery on Spotify
Shazia'Ayn Babul Desislava Hristova Antonio Lima Renaud Lambiotte Mariano Beguerisse-Díaz
We explore the social and contextual factors that influence the outcome of
person-to-person music recommendations and discovery. Specifically, we use data
from Spotify to investigate how a link sent from one user to another results in
the receiver engaging with the music of the shared artist. We consider several
factors that may influence this process, such as the strength of the
sender-receiver relationship, the user's role in the Spotify social network,
their music social cohesion, and how similar the new artist is to the
receiver's taste. We find that the receiver of a link is more likely to engage
with a new artist when (1) they have similar music taste to the sender and the
shared track is a good fit for their taste, (2) they have a stronger and more
intimate tie with the sender, and (3) the shared artist is popular with the
receiver's connections. Finally, we use these findings to build a Random Forest
classifier to predict whether a shared music track will result in the
receiver's engagement with the shared artist. This model elucidates which type
of social and contextual features are most predictive, although peak
performance is achieved when a diverse set of features are included. These
findings provide new insights into the multifaceted mechanisms underpinning the
interplay between music discovery and social processes.