Monday, 5 November 2012

The Key Opinion Leaders of Music

The evidence that ideas and fashions spread through society like viruses or like wildfire is compelling. Numerous studies have examined the networks in which this spread takes place and with increasingly large data sets to work with, researchers have become increasingly confident in their network-centric view of the world. These tools are teasing apart the large scale behaviour of humanity in ever increasing resolution. Our frequent viewers are well aware of the fact, the popculture is a futile ground for network analysis, whether it comes to movies, comics or music. 

Last.fm is interesting because it publishes lists of the most listened to artists divided geographically. So Lee and Cunningham have studied the way these charts vary in time and looked to see whether some cities consistently lead others in terms of listening habits. The researchers studied the Last.fm data for 200 cities around the world dating back to 2003. This is compiled from some 60 billion pieces of data the site collects from its users. 

Edges represent cities following.


The results are interesting. They show that certain cities appear to lead others for various genres of music. For example, Montreal seems to lead North American in indie music listening habits and the leader for hip hop is Atlanta. In Europe, Paris leads for indie music whereas Oslo leads for music as a whole. 

It's easy to imagine that the biggest cities ought to be those furthest ahead of the curve because they have biggest populations from which new and interesting bands can emerge. That doesn't seem to be the case in this data--big cities such as New York, LA and London do not lead. "We find only weak support for this hypothesis," say Lee and Cunningham. 

That may cause some alarm bells to ring. An interesting body of work has recently suggested that big cities benefit disproportionally for their size since qualities such as efficiency, productivity and innovation all scale super linearly with population. 

The ultimate test, of course, is whether their discovery has any predictive value. For example, could they predict how listening habits will change in the near future? "We have not yet demonstrated that our models have this predictive power, although we plan to attempt this validation in future work," they say.

Hooked already? Read the whole article on Cornell University's Library page.




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