As a cultural anthropologist, I have been involved in the study of alternative electronic dance music communities and event-based cultures. The Bandcamp Dance Librarian project grew out of this work. It uses the industry taxonomy of Beatport in an attempt to detect stylistic tendencies or repertoires within the Bandcamp libraries of (mainly) grasroots labels. The project output also show the tags (folksonomies) added by the artists/labels to the Bandcamp pages. It is therefore possible to compare the industry taxonomy of Beatport with artist folksonomies, as long as such tags are provided on Bandcamp, and eventually create a searchable system in this kaleidoscopic musical landscape, which can be especially useful for newcomer researchers, promoters, music exporters.
Forgetify is an application that is “recommending” you songs that have never been played on Spotify - not even by their families, friends or foes. When you design a recommendation engine for an artist or a label, you want to avoid that their songs ever arrive to Forgetify.
Big data creates injustice. We want to help small venues, independent small businesses, great artists and dedicated fans to make algorithms work for them. We create locally relevant recommendations and measure their effect.
I would like to use this example as a start of series how we are thinking about connecting musicians and their fans in new ways with the help of AI and big data. How we are planning to bring back life to the small venues after the pandemic? How we try to keep the link between musicians and their audience alive in this very sad year?