At work we have a lot of data about music popularity, and a growing amount of data about music genres, and a lot of data about time. Periodically some new way of combining these occurs to me.  

This week's is A Retromatic History of Music (or Love).  

 

This is an algorithmically-generated retroactive history of popular music. It is calculated by taking the 5000 most durably popular songs from each year since 1950 (using The Echo Nest's best guesses at both popularity and year), finding the genres to which their artists correspond (sometimes in hindsight), and then ranking those genres according to the fraction of that year's artists they each represent. This process is neither wholly accurate nor wholly precise, but neither is music, yet they both often seem to work.  

And although what results is wildly unglamorous in structure (it scrolls sideways!), and in some places obvious or dubious or both, maybe it's also one of these halting, anxious ways the computers have of trying to tell us that they understand not only what we love, but that we love.  

(For extra fun, use Control-F in your browser to highlight the rise and fall of particular genres.)