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Every Noice at Once VS MovieLens

Compare Every Noice at Once VS MovieLens and see what are their differences

Every Noice at Once logo Every Noice at Once

Every Noise At Once is a web app that lists every single music genre in an explorable, listenable...

MovieLens logo MovieLens

MovieLens helps you find non-commercial, personalized movie recommendations.
  • Every Noice at Once Landing page
    Landing page //
    2023-05-06
  • MovieLens Landing page
    Landing page //
    2023-07-23

Every Noice at Once videos

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MovieLens videos

Intro to Hadoop and Big Data: Part 3, The MovieLens Data Set

Category Popularity

0-100% (relative to Every Noice at Once and MovieLens)
Audio Player
100 100%
0% 0
Movie Reviews
0 0%
100% 100
Music
100 100%
0% 0
Movie Ratings
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Every Noice at Once seems to be a lot more popular than MovieLens. While we know about 422 links to Every Noice at Once, we've tracked only 19 mentions of MovieLens. 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.

Every Noice at Once mentions (422)

  • When do we stop finding new music?
    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 / 26 days ago
  • Spotify launches personalized AI playlists that you can build using prompts
    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 1 month ago
  • Displaying Content as a Graph
    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
  • The Beginning of the Past
    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 / 5 months ago
  • [OC] Exploring my world of music in 7 years of listening data
    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: 5 months ago
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MovieLens mentions (19)

  • Analyzing Real-Time Movie Reviews With Redpanda and Memgraph
    In this example, we will use the reduced MovieLens dataset streamed via Redpanda. Each JSON message will be structured like the one below:. - Source: dev.to / 11 months ago
  • DVDInbox - A new replacement service for Netflix DVD in the works
    Their rating & recommendation system is another top feature, in my opinion. The five-star rating system is superb. I think it was a major misstep when the streaming service switched over to the "thumbs up/down" system instead. Fortunately, the disc service retained the five-star system. I found the movie recommendation algorithm to be tremendously valuable. I don't think it would be too hard to build or even find... Source: 11 months ago
  • Alternatives to IMDB and Rotten Tomatoes for more realistic movie ratings?
    Https://movielens.org/ has an interesting concept and it has given me some recommendations that a traditional ratings site never would. Source: 12 months ago
  • CMV: When selecting a movie to watch, the audience's rating is the only thing that matters and the critic's rating is entirely irrelevant.
    Have you heard of movielens? They're doing something similar. Source: about 1 year ago
  • Blockbuster ‘laughed us out of the room,’ recalls Netflix cofounder on trying to sell company now worth over $150 billion for $50 million
    Checkout movielens if you miss the old Netflix rating system. It uses the same 5 star system and algorithm. https://movielens.org/. Source: about 1 year ago
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What are some alternatives?

When comparing Every Noice at Once and MovieLens, you can also consider the following products

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

Letterboxd - Letterboxd is a social site for sharing your taste in film, now in public beta.

Rate Your Music - Rate, list, and catalog music, videos, concerts, etc.

IMDb - Internet Movie Database

RadioGarden - An interactive map of live radio stations across the globe.

Simkl - Simkl is a TV, anime, and movie tracker that keeps a history of all the shows and movies you watch in one, central location. It’s a mobile app, a website, Google Chrome extension to keep track of everything you watch and integrates with many TV apps