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Analyzing the Bitcoin Network: The First Four Years

Author

Listed:
  • Matthias Lischke

    (Institute of Information Systems, Humboldt-Universität zu Berlin, Spandauer Str. 1, 10178 Berlin, Germany)

  • Benjamin Fabian

    (Institute of Information Systems, Humboldt-Universität zu Berlin, Spandauer Str. 1, 10178 Berlin, Germany)

Abstract

In this explorative study, we examine the economy and transaction network of the decentralized digital currency Bitcoin during the first four years of its existence. The objective is to develop insights into the evolution of the Bitcoin economy during this period. For this, we establish and analyze a novel integrated dataset that enriches data from the Bitcoin blockchain with off-network data such as business categories and geo-locations. Our analyses reveal the major Bitcoin businesses and markets. Our results also give insights on the business distribution by countries and how businesses evolve over time. We also show that there is a gambling network that features many very small transactions. Furthermore, regional differences in the adoption and business distribution could be found. In the network analysis, the small world phenomenon is investigated and confirmed for several subgraphs of the Bitcoin network.

Suggested Citation

  • Matthias Lischke & Benjamin Fabian, 2016. "Analyzing the Bitcoin Network: The First Four Years," Future Internet, MDPI, vol. 8(1), pages 1-40, March.
    • Handle: RePEc:gam:jftint:v:8:y:2016:i:1:p:7-:d:65233
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    References listed on IDEAS

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    1. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    2. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    3. Micha Ober & Stefan Katzenbeisser & Kay Hamacher, 2013. "Structure and Anonymity of the Bitcoin Transaction Graph," Future Internet, MDPI, vol. 5(2), pages 1-14, May.
    4. Hajime Inaoka & Takuto Ninomiya & Ken Taniguchi & Tokiko Shimizu & Hideki Takayasu, 2004. "Fractal Network derived from banking transaction -- An analysis of network structures formed by financial institutions --," Bank of Japan Working Paper Series 04-E-4, Bank of Japan.
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    Citations

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    Cited by:

    1. Valentina Gatteschi & Fabrizio Lamberti & Claudio Demartini & Chiara Pranteda & Víctor Santamaría, 2018. "Blockchain and Smart Contracts for Insurance: Is the Technology Mature Enough?," Future Internet, MDPI, vol. 10(2), pages 1-16, February.
    2. Nadia Pocher & Mirko Zichichi & Fabio Merizzi & Muhammad Zohaib Shafiq & Stefano Ferretti, 2023. "Detecting anomalous cryptocurrency transactions: An AML/CFT application of machine learning-based forensics," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    3. Bernhard Haslhofer & Burkhard Raunig & Pietro Saggase & Esther Segalla & Michael Sigmund & Felix Zangerl, 2023. "Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient? (Pietro Saggese, Esther Segalla, Michael Sigmund, Burkhard Raunig, Felix Zangerl, Bernhard Haslhofer)," Working Papers 248, Oesterreichische Nationalbank (Austrian Central Bank).
    4. Francisco Javier García-Corral & José Antonio Cordero-García & Jaime de Pablo-Valenciano & Juan Uribe-Toril, 2022. "A bibliometric review of cryptocurrencies: how have they grown?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    5. Natkamon Tovanich & Rémy Cazabet, 2022. "Pattern Analysis of Money Flow in the Bitcoin Blockchain," Post-Print hal-03896866, HAL.
    6. Natkamon Tovanich & R'emy Cazabet, 2022. "Pattern Analysis of Money Flow in the Bitcoin Blockchain," Papers 2207.07315, arXiv.org.
    7. Karau, Sören, 2021. "Monetary policy and Bitcoin," Discussion Papers 41/2021, Deutsche Bundesbank.
    8. Milena Oehlers & Benjamin Fabian, 2021. "Graph Metrics for Network Robustness—A Survey," Mathematics, MDPI, vol. 9(8), pages 1-48, April.
    9. Pietro Saggese & Esther Segalla & Michael Sigmund & Burkhard Raunig & Felix Zangerl & Bernhard Haslhofer, 2023. "Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?," Papers 2309.16408, arXiv.org, revised Apr 2024.
    10. Feyen,Erik H.B. & Kawashima,Yusaku & Mittal,Raunak, 2022. "Crypto-Assets Activity around the World : Evolution and Macro-Financial Drivers," Policy Research Working Paper Series 9962, The World Bank.
    11. George Vlahavas & Kostas Karasavvas & Athena Vakali, 2024. "Unsupervised clustering of bitcoin transactions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
    12. Bruzgė, Rasa & Šapkauskienė, Alfreda, 2022. "Network analysis on Bitcoin arbitrage opportunities," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. Trimborn, Simon & Peng, Hanqiu & Chen, Ying, 2024. "Influencer detection meets network autoregression — Influential regions in the bitcoin blockchain," Journal of Empirical Finance, Elsevier, vol. 78(C).

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