Collecting Data on Cryptoeconomic Systems
This week I’m focusing on research for the final project in my Modern Complexity Theory course. We’re being asked to write an essay which presents novel results on some topic related to the course. I’ve decided to work on measuring complexity in cryptoeconomic systems.
Complexity is widely recognized as an important characteristic of these systems, yet there is a notable lack of resources available for quantifying or categorizing specific relevant forms of complexity. Balaji Srinivasan’s 2017 statement on the importance of quantifying decentralization in blockchains holds equally true for the concept of complexity — “we must be able to measure it before we can improve it.”
I’ll share a full research update next week, but today I’m just going to share a bit about how I’m approaching data collection for the Bitcoin and Ethereum blockchains.
Energy Consumption
Energy is a key input for public blockchain networks. I’m using The University of Cambridge Center for Alternative Finance’s Bitcoin Electricity Consumption Index (Bitcoin) and Blockchain Network Sustainability Index (Ethereum) to collect estimated daily electricity consumption metrics for each blockchain.
Transaction Count
Blockchains are designed to facilitate transaction processing in a transparent and decentralized manner. So, measuring transaction counts provides insight into the pulse of the systems. It helps us evaluate the extent to which people are using them and at a more granular level, what people are using them for.
I’m utilizing data from Blockchain.com and Etherscan to gather daily transaction counts.
Node, Miner, and Validator Count
Nodes are computers which store copies of the blockchain while making sure that everyone follows the network’s consensus rules. They represent the backbone of decentralized blockchain networks. Miners (Bitcoin) and validators (Ethereum) are specialized nodes that are responsible for verifying transactions and adding them to the blockchain.
Looking at data about nodes and miners/validators helps us gain insight into the internal structure and power dynamics of these systems. How decentralized are they, and who holds power?
I’m using Bitnodes, Blockchain.com, Ethernodes and Beacon Chain to gather daily node, miner, and validator counts.
Next Steps
I’ve written a set of Python scripts that allow me to programmatically capture and store all of this information. My next steps are:
Optimizing my code.
Applying shannon entropy measures to my datasets as a first step towards measuring information-theoretic complexity.
Stay tuned for a much more detailed update next week.