Exponential growth

Are you a proponent of music fascism? I unfortunately wouldn’t be able to tell you, though luckily there is someone who might. Because this is precisely the question I asked myself this morning whilst re-fueling over my cafetière, around the same time as when I came across the work of a computer programmer from Colombia and a special calculator for the quandary at hand. For a while now I’ve been regularly running into the three-letter acronym ‘AEP’ around Last.fm — and after not paying it much attention at first, I soon decided that it was unlikely to mean ‘application environment profile’ given the particular context. Upon closer inspection, however, I discovered that it was in fact the abbreviation for a term coined by user C26000 (more commonly known as David Maya), referring to his anti-exponential points system. The AEP Calculator thus provides a way for Last.fm devotees to calculate what amounts to the numerical value of their music-listening habits in terms of multiformity and preferential bias. More simply, it measures how diverse your tastes in music are through factoring in the top fifty artists from personal audioscrobbled chart data as compiled in your user library.

The calculator itself was devised by Dave (alternatively davethemoonman), fashioned after Maya’s now ubiquitous formulaic points approach. The mathematics, in brief, can best be broken down as a function translating in what would visually appear as Malthusian growth (if you think back to the days of high school maths and recall what the graph of an exponential curve looked like, that’s basically what it amounts to). With a visual parallel drawn to Last.fm users’ charts, there is a curve as artist-counts gradually dwindle whilst going down in rank. Being ‘anti-exponential’ according to the system would then signify that your charted curve is less steep and therefore more diverse. And the formula, with the slope equivalent to the difference in value of the first artist in the chart and the fiftieth, is as follows: AEP = 5 – 25 x (slope ÷ average top 50 artists), with AEP often resulting as a value less than 5, with a 4 indicating rather diverse taste, a 3 standing at fairly diverse, and less than 0 indicating bias towards a tightly-niched handful of artists — or as Dave so eloquently puts it, ‘you only really like Britney Spears but occasionally you listen to other things’ or ‘have wide-ranging musical tastes but also a tendency to leave your MP3 player on repeat and go out to the pub’.

Depending on which end of the AEP spectrum you land, there are Last.fm groups you can join to specifically fit the bill: either (1) We Have Exponential Profiles, or (2) We Don’t Have Exponential Profiles. And as the latter of the two represents the flat-curvers of the bunch, it’s closed to anyone with an AEP value less than 4. So it would appear that an increase in exponential growth — also coincidentally referred to as exponential decay by math-wizards — could be a source of embarrassment because as Maya proclaims in the group’s description, ‘there are so many good artists out there to listen to just a few ones’. And I would agree entirely, though perhaps the bit of online audio-elitism between the two groups is what I find a tad unnecessary. But going back to the initial question in the debate that sparked it all, I am a music fascist only so far as 3.74 will take me, which makes me fall short just by a margin of 0.26 points in order to be granted access to the ironically exclusive anti-exclusive collective. It all reminds me of an opinion piece I had written back in September regarding a study that was widely publicised by the Associated Press relaying the work of Dr. Adrian North at Heriot-Watt University — a study which ultimately surmounted as an oversimplification of musical tastes in reflecting the very nature of who we are as individuals.

Yet though the AEP calculation is essentially a numerical simplification of musical inclination and diversity (especially once one considers the fifty-artist scope within which the function is bound), it provides positive empirical interpretation rather than normative statistical assessment. Today an increasingly popular tool as evidenced by the sheer number of users who now ‘wear’ their AEP count as badges on their profiles, the social music platform Last.fm has once more bridged the realms of music, psychology and social anthropology as users further elevate understanding of their music-listening activities to introspective, scientific levels. Albeit diversifying one’s collection does indeed take an entire lifetime in what would heftily add up to a costly endeavour in both time and pocket, it would not at all be ill-advised to branch out and diversify in order to see (or more importantly hear) what’s out there both past and present in the ever-expansive music archives. And for further musical self-analysis, Maya has also devised the handy, easy-to-use Last.fm Extra Stats programme for Windows.

Sarah Badr © MMVIII

See also: ‘In personal stereo’ (Last.fm Journal)

‘Love thy neighbour’ (pieces at random)


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