Abstrakt
Many music streaming portals recommend lists of songs to the users. These recommendations are often results of black-box algorithms (from the user's perspective).
However, irrelevant recommendations without the proper justification may considerably hinder the user's trust. Moreover, user profiles in music streaming services tend to be very large, consisting of hundreds of artists and thousands of tracks.
So, not only the recommendation procedure details are hidden for the user, but he/she often lacks a sufficient knowledge about the source data the recommendations are derived from. In order to cope with these challenges, we propose SpotifyGraph application.
The application aims on a comprehensible visualization of the relations within the Spotify user's profile and therefore improve understandability of provided recommendations.