It’s been a while since I posted some cool data visualisation things here, so here’s a treat from Anonymous Prof, who has been busy mapping Last.fm.
The post about the networks is worth a read. Anonymous Prof used the Last.fm API to gather his data and started to build visualisations of the networks, including some interesting observations about “outliers”, small networks of users isolated from the main community.
And his ambitions don’t stop there:
I’m also beginning to collect the listening history of users (again thanks to the wonderful API) and hope to examine music listening patterns as they relate to the network. That’ll be a much bigger problem because of the volume of data. I collected a small amount just to see what it would look like and for the 183 users that I checked, I already have 1,179,480 track plays. Scaling up to ~300k users is a bit much. Regardless, I may use the friends data to identify a sub-network of friends and track their listening patterns to see how they influence one another.
Now that could be seriously interesting – I’m subscribed and look forward to hearing more about his adventures with that network.
Via Data Mining