The data visualisation shows your music archive where only the songs are shown which you added to your playlists.
Every song is described by seven categories. Each category has its own colour:
shows how acoustic a song is.
classifies the mood of a song into a spectrum from 0 to 1 and respectively from sad to happy.
represents the intensity and activity of a song.
registers how live a song is and is able to identify audience sounds in a recording.
describes how danceable a song is.
analyses the song to distinguish between spoken words and singing.
addresses the parts without singing or spoken words, the instrumental parts, of a song.
Every category consists of 100 values between 0 and 1, in which 1 stands for the highest intensity.
Each value is displayed as an own circle. The number of songs which share the same value in the same category define the diameter of the circle:
= 50 songs with the same value in the same category
= 5 songs with the same value in the same category
The closer the value reaches to 1, the higher the frequency in sound and scaling gets:
Click When a circle gets clicked on its related circles are shown in their particular category colour.
Circles that are unrelated to the selected circle retreat into the background.
Hover A circle shows his music attributes when active and hovered over.
We are living in an increaslingly digitised world but most of us barely have any background knowledge about digital processes. Due to the digital age streaming services gradually evolve. Music streaming services like Spotify massively changed the music industry and the musical behaviour of their users. Current studies show that the individual musical behaviour turns away more and more from criteria such as genre or artists. The once established criteria seem to get replaced by intelligent algorithms that work in the background.
Spotify is for most of its users what you call a "black box", which means that people without any expert knowledge are not able to understand what kind of processes are going on in the technical background of the application. This interactive data visualisation was created to make Spotify more transparent for its users.
Klangspektrum enables Spotify users to analyse their musical behaviour based on simplyfied algorithmically calculated song attributes. The user should be able to establish a relation between already familiar parameters such as songs and genres and the abstract song values. Metaphorically speaking the observer transforms into an algorithm to analyse his /her own music profile.
The digital age has long arrived in the music industry and brought a lot of change for listeners as well as artists.
Current studies show that the individual musical behaviour increaslingly turns away from criteria such as genre or artists.
The once established criteria seem to get replaced by intelligent algorithms that work in the background. In the following application you can gain insights into these background processes.