In brief, Music Neighbourhood is a pretty visualisation that connects artists with a high ‘similarity score’, allowing you to dynamically move from artist to artist, exploring their connections. Similarity score is a system that uses listener data to find similar artists, based on listener data, which has already seen use in our Fresh Releases and the LB Radio beta.
Music Neighbourhood also has a few other interesting things under the hood - for instance, it makes use of ‘Huesound’ to dynamically change colours based on the artist’s top album art.
Why is this of interest to hackernews? As with everything MetaBrainz creates, this is open-source, and we would love to see Music Neighbourhood, or elements of it, pulled into other projects or hacked into something new! The depth of MusicBrainz and ListenBrainz data allows for a lot of expansion on the concept - for instance, exploring based on genre, popularity, or listeners, and different ways of presenting clusters and datapoints. We expect to keep building on Music Neighbourhood ourselves, time allowing, as well.
Music Neighbourhood also has a few other interesting things under the hood - for instance, it makes use of ‘Huesound’ to dynamically change colours based on the artist’s top album art.
Why is this of interest to hackernews? As with everything MetaBrainz creates, this is open-source, and we would love to see Music Neighbourhood, or elements of it, pulled into other projects or hacked into something new! The depth of MusicBrainz and ListenBrainz data allows for a lot of expansion on the concept - for instance, exploring based on genre, popularity, or listeners, and different ways of presenting clusters and datapoints. We expect to keep building on Music Neighbourhood ourselves, time allowing, as well.