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Electronic Commerce Research and Applications
Volume 24, July–August 2017, Pages 23-29
Digital blockchain networks appear to be following Metcalfe’s Law
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Public ledger systems provide us a wealth of information for their network analysis.
Network effects on the growth of some of the networks was confirmed.
A new network model presented here modeled the networks well as did Metcalfe’s law.
The network’s value was related to the exponential of the root of its active users.
The mathematical form of the model allows for new ways of analyzing the networks.
An analysis of some of the recent blockchain networks is presented to determine if they satisfy Metcalfe’s Law, as has been shown for some online social media networks. The value of the network was modeled based on the price of the digital currency in use on the network, and the number of users by the number of unique addresses each day that engage in transactions on the network. The Bitcoin, Ethereum, and Dash networks were analyzed. The analysis shows that the networks were fairly well modeled by Metcalfe's Law, which identifies the value of a network as proportional to the square of the number of its nodes, or end users. A new network model was also presented that shows the value to be proportional to the exponential of the root of the number of users participating in the network, and shows good agreement as well. Conditions for determining critical mass based on the new model were also presented. Finally, the potential for identifying value bubbles that can be spotted as deviations in value from the model was discussed and illustrated using the data from one of the networks. Those value bubbles show up where repeated extremely high value increases are not accompanied by any commensurate increase in the number of participating users, or any other development that could give rise to the higher value.
Digital networks​
Distributed ledger systems
Distributed transaction processing​
Metcalfe’s Law
Network effects
Online payments
Payment networks
Ken Alabi has a Ph.D. in Engineering from Stony Brook University and a Masters in Computer-Aided Engineering from the University of Strathclyde. He is a programmer and technology professional with over thirty publications in the fields of Engineering and Computer Science.
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