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May 19, 2005

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» Friday, May 20, 2005 10:45 PM from Critical Section
The popularity of "stuff" in a market area seems to follow a power-law distribution. Clay Shirkey had done some interesting analysis of power laws, which Chris Anderson summarizes in a power-law primer. "Powerlaw distributions occur where things are... [Read More]

» Who's wagging the long tail? from Blog Business Summit
The author of the longtail blog an forthcoming book posts on how the theory is indeed “full of crap” and at the same time brilliant. The long tail is about “how the mass market is turning into a million... [Read More]

Comments

Randall Newton

Chris, I was fascinated by your original Wired article, and have been following LT since. I remember in the dotcom boom days, everybody talked about S-curves for product implementations. Is there a fundamental relationship between the S-curve and the LT curve?

chris anderson

Randall,

As as best I understand the S curve, it's unrelated. It's primarily a learning curve that takes a while to get traction, climbs steeply, and then levels off. No connection to the above, unless I'm really missing something.

Kevin Marks

Chris, power law distributions occur lots of other places too, in nature as well as in human-mediated areas. I can recommend "Ubiquity : Why Catastrophes Happen" by Mark Buchanan) for a discussion of this, including earthquakes and cities as 2 other examples.
Mandelbrot's Fractal Geometry of Nature discusses scale-free distributions at some length too.

John Thacker

The rules you've stated, however, are not sufficient for a power-law distribution. They are hypothesized as explanations for why we appear to get heavy-tailed distributions when studying Internet effects, but have not been conclusively proven. There are many, many distributions which look similar to power-laws, at least with small amounts of data. Power laws look like best fits in many cases, but there are other possibilities. One can look at the immense amount of discussion I saw at a recent conference at Cornell on heavy tailed distributions, and disagreement over whether particular phenonema actually had them.

An exponential distribution can look like a Pareto; the difference occurs out in the tails, and thus it takes a lot of careful data in order to be sure that one has a Pareto and not an exponential or something else. There are lots of non-heavy tail distributions.

Your last paragraph is confusing. Even in the non-heavy tail distributions there are network effects, success breeds success, and so on. It's possible that network effects can happen in such a way that the area under the tail becomes so small that it's not significant. That the Internet and everything else will not cause a revolution because the tail is too small. That things are like
ketchup
, not mustard.

T Neville

Chris

I think Clay’s passing reference to the psychic allure of “solidarity goods” – of reading the same blogs as your friends – reveals a lot about why audiences cluster around a small number of available information/entertainment products.

When talking about media, especially electronic media, the “currency” value of sharing the same media experience at the same time has substantial social and commercial cachet.

This is why broadcast media had such a profound impact on social organization. It’s also why advertisers eagerly pay more (on a CPM basis) for large broadcast audiences who see their ads at the same time.

Marshall McLuhan recognized this too. He defined the term “mass media” as refering not to “the size of their audiences, but of the fact that everybody becomes involved with them at the same time.”

Deus ex Machina

I dont think its overly relavent if a distribution is strictly pareto or only exponential. the point is that vast inequality of outcome arise from incremental changes in differentiation.

the driving factor behind this outcome are really only 2 points: differentiation between producers and freedom of choice on the consumer side.

the efficiency of how information spreads seems to only have an effect on the time for a resulting pareto concentration.


Manish Danani

Hi,

I would like to know how the formula of powerlaw really works? What is the exponent that one uses and why? Would appreciate if you can throw some light on that.

Regards,

Manish
ERP & EAI Specialist
http://www.dcs.bbk.ac.uk/~ldana01/

cheap eve isk

I dont think its overly relavent if a distribution is strictly pareto or only exponential. the point is that vast inequality of outcome arise from incremental changes in differentiation.

the driving factor behind this outcome are really only 2 points: differentiation between producers and freedom of choice on the consumer side.

the efficiency of how information spreads seems to only have an effect on the time for a resulting pareto concentration.

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Tidbits

The Long Tail by Chris Anderson

Notes and sources for the book

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