Last.fm can already recommend the most compatible festivals based on your current music taste, but what about discovering new music? We decided to use a bit of 10% time* to see if Last.fm listening data could be used to recommend the best festivals for seeing the future stars of summer 2012.
@Omar711, Last.fm’s data scientist, started by looking at new artists playing in festivals this summer to see which have a high “hype score”. Hype is our measurement of how fast an artist’s audience is growing over a short period of time. Then Omar looked at historical data for all festivals over the last few years to see how many artists had become successful (i.e. grew in audience) directly following the festival. This gave us a ranking of how influencial festivals were in growing new artists. We pulled out the top 10 for our infographic, and then highligthed the artists with the most hype.
As we tend to call artists that have big audiences “stars” I thought I would use stars in my infographic (I find these dazzling leaps of lateral thinking exhausting). The hype scores would be represented as the brightness of the star. However, when I tried to convert the hype scores into percentages to scale the circles in my infographic, some were massive and other came out microscopic. So I called Omar over and he said “ah yes, skewed distrubution. Just use log or square root”.
It must be strange for Omar to be working so closely with an idiot. A short math lesson later and I had a nice range of percentages to play with (and I felt a bit smarter, almost ready for my own PHD ;).
* staffers are given 10% of their time to work on self-driven projects, providing the work is related to music data (I have been told off for spending too much time working on a diorama of Jabba’s palace for my Star Wars figures)