The context in which people listen to music has been the object of study of a growing number of publications, particularly coming from the field of music psychology. Konecni has suggested that the act of music listening has vacated the physical spaces devoted exclusively to music performance and enjoyment long ago and that music nowadays is listened to in a wide variety of contexts.
As music increasingly accompanies our everyday activities, the music and the listener are not the only factors, as the context of listening has emerged as another variable that influences and is influenced by the other two factors. It has been also observed that people consciously understand these interactions and use them when choosing music for daily life activities. The context of music listening seems to influence the way in which people choose music, and so music recommenders should suggest music items to fit the situation and needs of each particular listener.
I would track all of your users' listening habits in a central database, so you can make recommendations based on what other people like too ("people that liked this song, also liked these other songs")
some other metrics to consider:
also:
what volume do they play the song? do they crank it up?
Put in a "recommend this song to friends" button (that emails song title to a friend or something). Songs they recommend, they probably like.
You can refer the following link for better understanding:
https://pdfs.semanticscholar.org/fc45/45d0fcd0b8db487b5606febbe6fbd36ffd4d.pdf
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