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It's an interesting thesis, but I'm a bit confused by your methodology - how can you propose a law without looking at any data yourself? You just seem to collec

by t_mann 4y ago

It's an interesting thesis, but I'm a bit confused by your methodology - how can you propose a law without looking at any data yourself? You just seem to collect a few unrelated observations ("librarians have observed X", without giving any reference there) and laws that were developed for different contexts (Zipf's law), and from there you argue your way quite informally (mathematically speaking) to your proposed n log(n) formula. Sorry for being so critical, but I would find it quite interesting if you had hard evidence to support a scaling law like n log(n) for the value of a social network.

btilly 4y ago
We were applying a variety of other scaling phenomena which have been long observed, and then applied it in terms of networks. Most of the actual analysis of data, such as mail delivery was done by Andrew Odlyzko. There is also another form of the paper out there with Bob Briscoe added, and he had quantitative data not previously published from British Telecom. (See https://spectrum.ieee.org/metcalfes-law-is-wrong https://spectrum.ieee.org/metcalfes-law-is-wrong for a link, but you'll need a subscription.) That said, the argument and result is intentionally informal, and intended to be a better rule of thumb than Metcalfe's law. Which was itself even more informally reasoned. However its key flaw we explained with: Metcalfe’s Law is intuitively appealing, since our personal estimate of the size of a network is based on the uptake of that network among friends and family. Our derived value also varies directly with that metric. We therefore see a linear relationship between the perceived size and value of that network. That said, different social networks may well have different scaling laws. In fact I pointed out privately that eBay likely was a counter-example which is closer to Metcalfe's law for the simple reason that you derive value there from connections to random strangers. And indeed eBay successfully maintained a market leading position for a long time despite charging significantly higher fees than competitors like Amazon Marketplace.

by t_mann 4y ago

btilly 4y ago

We were applying a variety of other scaling phenomena which have been long observed, and then applied it in terms of networks. Most of the actual analysis of data, such as mail delivery was done by Andrew Odlyzko. There is also another form of the paper out there with Bob Briscoe added, and he had quantitative data not previously published from British Telecom. (See https://spectrum.ieee.org/metcalfes-law-is-wrong https://spectrum.ieee.org/metcalfes-law-is-wrong for a link, but you'll need a subscription.) That said, the argument and result is intentionally informal, and intended to be a better rule of thumb than Metcalfe's law. Which was itself even more informally reasoned. However its key flaw we explained with: Metcalfe’s Law is intuitively appealing, since our personal estimate of the size of a network is based on the uptake of that network among friends and family. Our derived value also varies directly with that metric. We therefore see a linear relationship between the perceived size and value of that network. That said, different social networks may well have different scaling laws. In fact I pointed out privately that eBay likely was a counter-example which is closer to Metcalfe's law for the simple reason that you derive value there from connections to random strangers. And indeed eBay successfully maintained a market leading position for a long time despite charging significantly higher fees than competitors like Amazon Marketplace.