Based on our record, Every Noice at Once seems to be a lot more popular than Spotify Artists. While we know about 422 links to Every Noice at Once, we've tracked only 12 mentions of Spotify Artists. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
You probably need to sign up for Spotify for Artists: https://artists.spotify.com/home. Source: almost 2 years ago
Check out https://artists.spotify.com/ if you want to know how it works. Source: about 2 years ago
You should be able to claim your Spotify artist page by heading to https://artists.spotify.com/ and following the steps there. Source: about 2 years ago
Both artists and managers can submit an artist to be considered for verification. First, you need to go to Spotify for Artists and click “Claim Your Profile.”. Source: about 2 years ago
Https://artists.spotify.com/ make sure you're not signed in to this page. Click on upper right to gain access to new artist page. Source: over 2 years ago
I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / about 1 month ago
Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / about 2 months ago
The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 5 months ago
This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 6 months ago
Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 6 months ago
Level Music - A new platform for independent artists, everywhere. In beta.
Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm
UnitedMasters - Creator tools for artists to get smart, get fans, get paid
Rate Your Music - Rate, list, and catalog music, videos, concerts, etc.
Apple Music for Artists - Artist analytics and management suite for Apple Music
RadioGarden - An interactive map of live radio stations across the globe.