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Archive for the 'self-indulgent nerdism' Category


Join the dots

June 13th, 2008 / 7 Comments »

Sitting in a soul-destroying traffic jam in Moate the other day, I realised that the design of cars is basically broken:

1.
Metcalfe’s Law says that the value of a network increases in proportion to the number of nodes in that network. The canonical example is a global network of fax machines: one fax machine on its own is useless, two fax machines linked together is pretty useful, and a worldwide network of fax machines is incredibly useful. The more fax machines that get added to the network, the more powerful the network is.

2.
The theory goes that this applies to online social networks too (the more people in the network, the more value it offers to each member), but in practice the overcrowding of social networks can lead to a noisy, jammed experience. Having many other nodes available to an individual user is indeed valuable, but having all of those nodes exposed is not very scalable for the user, who has to pay attention to them all. So a well-designed network protects users by allowing them to selectively filter out most of the irrelevant noise, setting their own threshold and listening to only some of the other nodes.

3.
A network externality is the consequence of a transaction that indirectly affects an individual. No wait, come back! Network externalities are just a way of explaining the indirect knock-on effects of something happening — sort of like the butterfly effect in reverse, with the outcomes of everything else that’s going on combining to affect you individually. Positive network externalities are when these outside network activities have the effect of providing you with a better experience, and negative externalities result in a worse experience.

4.
Roads are networks, and cars are the nodes that operate on those networks. There would be hardly any roads without cars, and cars would be almost useless without any roads. Especially considering the fact that car taxes are used to build roads, having more cars out there helps to create a mutually beneficial system for all drivers, by creating the infrastructure from the sum of all road users’ contributions. So more cars equals positive network externalities. But then there comes a point at which roads become overloaded with cars, and the value that the network provides to individual nodes begins to reduce. For cars, Metcalfe’s Law is in fact a bell curve that peaks at some happy medium of free-flowing cars on good quality roads, and descends steadily to eventually arrive at some point on the N6 heading east just outside Moate.

5.
Therefore cars, as network objects, are intrinsically broken. Maybe not quite broken, because they still work to some extent, but after a point they definitely suffer from negative externalities as more nodes are added to their system. But despite the fact that cars are social objects, they have not at all been designed as such. Bound to the physical world, they can’t provide you with any way of setting a threshold and insulating yourself from an overloaded network the way a decent social network might. And that’s why the user experience of driving a car is often so shitty. Looking at it this way, the more nodes you add to the network, the less effective they individually become.

6.
Thankfully I got out of Moate at around this point, so I wasn’t obliged to continue this train of thought any further and actually come up with solution. Not that I could. I suspect there isn’t one, and that’s why I said cars may be *intrinsically* broken. Public transport that works is a good bet, but is hard. MapReduce for travel? Or maybe public transport only needs to be better than cars; it isn’t right now, but as cars get worse public transport might become more attractive. That’s not really a solution though. There’s certainly lots of room right now for more intelligent cars that diminish the impact of heavily-loaded networks. Interconnected SatNav magic could divert cars along the most efficient route. Analysing traffic jams shows that they can occur just because of human driving styles that can be easily avoided with a little mediation.

7.
Some caveats: The network itself can and should be better designed to handle larger capacities, but the design of roads is constrained by geography and there is always going to be a breaking point. Scaling is hard (just ask the Twitter guys). There are some small practical changes being made to the design of cars (smaller cars in cities, for example), but really cars as functional devices have changed almost imperceptibly over the last hundred years. And as petrol becomes an ever more scarce commodity that an ever-increasing number of cars are all vying for, which in turn drives the price of petrol further up for individual car owners… well, you get the idea. Bravery in car design may only arrive when forced, and when the problem of too many cars on the road is threatened with extinction.



1000 bookmarks

April 13th, 2008 / 3 Comments »

This week I dinged a thousand bookmarks on del.icio.us and thought it might be interesting to examine how I’ve used the service over the last couple of years. Firstly, some raw data:

  • I’ve posted 1000 bookmarks since 25th March 2004. That’s 1480 days ago, so I posted an average of 4.73 bookmarks a week.
  • Amazingly, I used 999 distinct tags, so obviously I’m introducing an average of one new tag for every bookmark. 568 tags are used only once. The most-used tag is design, appearing on 104 bookmarks.
  • The number of tags on individual bookmarks ranges from 1 (on 11 bookmarks) to 15 (on 1). There are 4702 tags in all (including duplication across different bookmarks), and so each bookmark has an average of 4.7 tags.

I guess the most noteworthy thing out of all of that is the coincidental near-exact matching of the number of bookmarks with distinct tags (1000/999), and the average bookmarks per week with average tags per bookmark (4.73/4.70). I have no idea if this really is just a coincidence or an effect of some unconscious underlying usage pattern.

Here’s the frequency of my posting those thousand links:

Graph of number of bookmarks over time

Here are my top 10 tags of all time:

Bar chart of top 10 tags

But really, the commonly used tags are only a small part of the data compared to the long tail of little-used tags. The same top ten tags are to the left of the vertical blue line on this chart showing the number of times each tag was used:

Distribution of tags

There’s lots more that could be read from a dataset this size; it would be nice if del.icio.us actually did some of these calculations for you. I made these charts with the del.icio.us API, Google Charts API, and the handy Python Google Chart wrapper. Congratulations to Mr. Chuck Klosterman of Esquire Magazine (whose book I’m also reading right now) on being my 1000th customer.