The Complex Community Structure of the Bitcoin Address Correspondence Network
Jan Alexander Fischer, Andres Palechor, Daniele Dell'Aglio, Abraham, Bernstein, Claudio J. Tessone

TL;DR
This paper analyzes the complex topology of the Bitcoin Address Correspondence Network, revealing statistical regularities that improve entity identification and deepen understanding of Bitcoin's usage patterns.
Contribution
It is the first to analyze the complex topology of the Address Correspondence Network and demonstrates how community detection can reliably identify entities.
Findings
Network exhibits a skewed degree distribution and power-law component sizes.
Combining external data with community detection improves entity identification.
Regularities in usage patterns reveal insights into the Bitcoin economy.
Abstract
Bitcoin is built on a blockchain, an immutable decentralised ledger that allows entities (users) to exchange Bitcoins in a pseudonymous manner. Bitcoins are associated with alpha-numeric addresses and are transferred via transactions. Each transaction is composed of a set of input addresses (associated with unspent outputs received from previous transactions) and a set of output addresses (to which Bitcoins are transferred). Despite Bitcoin was designed with anonymity in mind, different heuristic approaches exist to detect which addresses in a specific transaction belong to the same entity. By applying these heuristics, we build an Address Correspondence Network: in this representation, addresses are nodes are connected with edges if at least one heuristic detects them as belonging to the same entity. %addresses are nodes and edges are drawn between addresses detected as belonging to…
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