Mining Cultural Music Listening Behavior
Independent of the society or culture, people enjoy to listen to music worldwide. However, there might me differences in the music consumption behavior depending on the cultural embedding of the users. In the field of music information retrieval, a lot of effort was put on how to represent music as numbers. Nowadays, signal processing allows to characterize music by its content. However, less effort was put on how culture can be represented in numbers. Goal of this bachelor project is to merge existing data sets describing the music consumption behavior of music streaming platform users with socio-economic data sets reflecting cultural characteristics. Aiming at characterizing cultural music listening behavior, different pattern mining techniques are applied to this data set in a second step.