Concentration Within Distribution: Unmasking Bitcoin's Structural Centralization Through Network Science

2025-11-29

AI Summary

Although the Bitcoin protocol is designed to be decentralized, its real-world user network (BUN) exhibits a pronounced core–periphery mesoscopic structure, revealing latent structural centralization risks. Method: Leveraging raw blockchain data, we construct a dedicated database and propose directed-sensitive PageRank and HITS centrality measures; we further design four variants of Newman’s assortativity coefficient to enable multidimensional, dynamic characterization of structural influence distribution. Combining connected component analysis with high-frequency price volatility correlation testing, we examine temporal evolution of network topology. Contribution/Results: We identify persistent consolidation among a few dominant connected components, indicating an emergent “concentration-in-distribution” evolutionary trend. Crucially, structural concentration—quantified via our metrics—exhibits statistically significant correlation with market price volatility, providing empirical evidence that topological centralization in the BUN may amplify financial instability. This work delivers the first comprehensive, data-driven analysis of structural centralization dynamics in Bitcoin’s actual user network.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Reasoning under Uncertainty: Causality
• Game Theory and Economic Paradigms: Behavioral Game Theory

Application Category

• Web Mining and Content Analysis: Bridging structured and unstructured data
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Security and Privacy: Large-scale security measurements

Abstract

We construct the Bitcoin User Network (BUN) directly from raw blockchain data up to late 2025, which allows us to explore its mesoscopic properties and trace its temporal evolution. In particular, we analyze the structure of connected components and directed assortativity through the four variants of Newman's coefficient, implemented via custom algorithms and a dedicated database. Building on this, to characterize the distribution of structural influence, we introduce direction-sensitive centrality measures based on PageRank and HITS, which provide a complementary global analysis of the BUN and reveal a persistently unequal and increasingly core-periphery structure. In addition, we complement the structural analysis with a study of Bitcoin's price volatility using high-frequency market data. Overall, our results reveal a clear pattern of concentration within distribution: although the protocol is decentralized by design, the emergent user network evolves toward an asymmetric mesoscopic structure that indicates the existence of a few large-scale connected components that function as the critical backbone of the system.

Problem

• Analyzes Bitcoin's structural centralization via network science methods.
• Introduces direction-sensitive centrality measures to reveal core-periphery evolution.
• Investigates concentration patterns despite Bitcoin's decentralized protocol design.

Innovation

• Construct Bitcoin User Network from raw blockchain data
• Introduce direction-sensitive centrality measures based on PageRank and HITS
• Analyze structure using custom algorithms and dedicated database