Posts Tagged wisdom of the crowds
At music sites like Rdio and Spotify, music fans have been creating and sharing music playlists for years. Sometimes these playlists are carefully crafted sets of songs for particular contexts like gaming or sleep and sometimes they are just random collections of songs. If I am looking for music for a particular context, it is easy to just search for a playlist that matches that context. For instance, if I am going on roadtrip there are hundreds of roadtrip playlists on Rdio for me to chose from. Similarly, if I am going for a run, there’s no shortage of running playlists to chose from. However, if I am going for a run, I will need to pick one of those hundreds of playlists, and I don’t really know if the one I pick is going to be of the carefully crafted variety or if it was thrown together haphazardly, leaving me with a lousy playlist for my run. Thus I have a problem – What is the best way to pick a playlist for a particular context?
Naturally, we can solve this problem with data. We can take a wisdom of the crowds approach to solving this problem. To create a running playlist, instead of relying on a single person to create the playlist, we can enlist the collective opinion of everyone who has ever created a running playlist to create a better list.
I’ve built a web app to do just this. It lets you search through Rdio playlists for keywords. It will then aggregate all of the songs in the matching playlists and surface up the songs that appear in the most playlists. So if Kanye West’s Stronger appears in more running playlists than any other song, it will appear first in the resulting playlist. Thus songs, that the collective agree are good songs for running get pushed to the top of the list. It’s a simple idea that works quite well. Here are some example playlists created with this approach:
Best Running Songs
Sad Love Songs
This wisdom of the crowds approach to playlisting isn’t limited to contexts like running or coding, you can also use it to give you an introduction to a genre or artist as well.
The Smart Playlist Builder
The app that builds these nifty playlists is called The Smart Playlist Builder. You type in a few keywords and it will search Rdio for all the matching playlists. It will show you the matching playlists, giving you a chance to refine your query. You can search for words, phrases and you can exclude terms as well. The query sad “love songs” -country will search for playlists with the word sad, and the phrase love songs in the title, but will exclude any that have the word country.
When you are happy with your query you can aggregate the tracks from the matching playlists. This will give you a list of the top 100 songs that appeared in the matching playlists.
If you are happy with the resulting playlist, you can save it to Rdio, where you can do all the fine tuning of the playlist such as re-ordering, adding and deleting songs.
The Smart Playlist Builder uses the really nifty Rdio API. The Rdio folks have done a fantastic job of giving developers access to their music and data. Well done Rdio team!
Go ahead and give The Smart Playlist Builder a try to see how the wisdom of the crowds can help you make playlists.
When I test-drive a new music recommender I usually start by getting recommendations based upon ‘The Beatles’ (If you like the Beatles, you make like XX). Most recommenders give results that include artists like John Lennon, Paul McCartney, George Harrison, The Who, The Rolling Stones, Queen, Pink Floyd, Bob Dylan, Wings, The Kinks and Beach Boys. These recommendations are reasonable, but they probably won’t help you find any new music. The problem is that these recommenders rely on the wisdom of the crowds and so an extremely popular artist like The Beatles tends to get paired up with other popular artists – the results being that the recommender doesn’t tell you anything that you don’t already know. If you are trying to use a recommender to discover music that sounds like The Beatles, these recommenders won’t really help you – Queen may be an OK recommendation, but chances are good that you already know about them (and The Rolling Stones and Bob Dylan, etc.) so you are not finding any new music.
At The Echo Nest we don’t base our artist recommendations solely on the wisdom of crowds, instead we draw upon a number of different sources (including a broad and deep crawl of the music web). This helps us avoid the popularity biases that lead to ineffectual recommendations. For example, looking at some of the Echo Nest recommendations based upon the Beatles we find some artists that you may not see with a wisdom of the crowds recommender – artists that actually sound like the Beatles – not just artists that happened to be popular at the same time as the Beatles. Echo Nest recommendations include artists such as The Beau Brummels , The Dukes of Stratosphear, Flamin’ Groovies and an artist named Emitt Rhodes. I had never ever seen Emitt Rhodes occur in any recommendation based on the Beatles, so I was a bit skeptical, but I took a listen and this is what I found:
Update: Don Tillman points to this Beatle-esque track:
Emitt could be the sixth Beatles. I think it’s a pretty cool recommendation