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.

我们通过使用来自Spotify的数据，研究了影响人与人之间音乐推荐和发现结果的社会和环境因素，发现接收者与分享者的音乐品味相似、分享的歌曲适合接收者的口味、接收者与分享者的联系较强以及分享的艺术家受到接收者关注的程度是接收者与新艺术家互动的重要要素，并构建了一个随机森林分类器来预测分享的音乐是否会引起接收者与分享的艺术家之间的互动。这些研究结果揭示了音乐发现和社会过程之间多方面机制的新见解。

链接我再次宝贝：Spotify上的社交音乐发现