90-9-1 Community!

As described here before [1], power laws are very potent at describing many type of phenomena. Latest principle is the 90-9-1 principle of online communities [2].

The concept is simple. In an online community, 1 percent are creators of content, 9 percent are editors of content and the remaining 90 percent are just the curious audience watching. The phenomenal thing is that this rule seems to be proportional, so that getting more creators to a site, increases the editors and the audience.


My bet is that many users act in different roles depending on the site they use, but that there is a small minority of heroes out there that generates most of the community content - and hence drives the traffic.


[1] The Vital Few or the Trivial Many?
[2] 90-9-1 Principle

The Vital Few or the Trivial Many?

When the Pareto Principle [1] was popularized within business and engineering in the 1940s by Dr. Joseph Juran, he called his theory "The Vital Few and the Trivial Many" [3] : A few vital inputs produce most of the results. For many years now that has been how we are taught to prioritize ideas and activities in business. However, thanks to the Internet, the Pareto Principle is being falsified [4] in various domains.
The insight comes from power law theory [2]. As one can see in the figure to the right (from wikipedia) , a power law distribution can be split into a vital few (the green area) and the trivial many (the yellow). What is happening for many products and services sold via the Internet is that demand is shifting down the tail - making the tail fatter and the head slimmer! According to [5] there are 3 reasons for this:

1. Cost of production of many products from music and books to Internet services is falling, thereby creating more available products in the tail.
2. Cost of inventory and distribution is falling though JIT production, digital content and application hosting. The marginal cost of one more product ore product feature in the inventory is extremely small, making it profitable for low volume sales of one item.
3. The Internet and it's search engines and communities are creating new ways for consumers and businesses to find more specialized products and solutions that fit their exact tastes and needs.
   

This insight is rather extraordinary because it shows that lucrative business opportunities exist where there was said to be none. Furthermore, there are signs that the profit margin is larger and the competition smaller at the tail per unit than at the head. Sounds like faster money to me!

[1] The Pareto Principle
[2] Power Laws and Long Tails
[3] The Vital Few and the Trivial Many (external)
[4] Falsifiability (external)
[5] The Long tail (exteral)

Power Laws and Long Tails

The standard normal distribution (bell curve) is today dominant when we model phenomena. It often works out quite nicely with reality, but it has one easily to forget limitation : It assumes that the occurrences are independent. In many cases independence is very limiting. Interdependence needs to be taken in account. In these cases power laws are more accurate (For a definition of a power law see [1]). The result is that extreme events become much more probable.

Look at the diagram below from [3] (also a great overview of power laws). As you can see, a bell curve will predict that unlikely events are very rare. In cases of independence of phenomena that is likely. A power law distribution looks similar, but has a "fat tail". The implication is that it predicts that rare events are much more likely (you may say that the interdependence creates a possible "butterfly effect").





An example from [2] (a brilliant book by the way) is illustrative. In the book business, the largest brick and mortar shops can keep an inventory of maximum 100.000 books. After that the business of keeping them in store becomes unprofitable. A site like Amazon.com has an inventory of over 1.5 million books and growing. Even though it sells only a a few copies of the millionth popular book, it still makes a profit on it. That's due to the low costs of storage, distribution and sales.

An example from [3] is another illustration : "In the case of market fluctuations, for example, the bell curve predicts a one-day drop of 10 percent in the valuation of a stock just about once every 500 years. The empirical power law gives a very different and more reliable estimate: about once every five years." As the reader may know, we see 10 percent drops fairly often!

[1] Wikipedia - Power Law
[2] The Long tail
[3] Power Laws & the New Science of Complexity Management