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Visualizing and Analyzing Entity Activity on the Bitcoin Network

Abstract : We present BitConduite, a visual analytics tool for explorative analysis of financial activity within the Bitcoin network. Bitcoin is the largest cryptocurrency worldwide and a phenomenon that challenges the underpinnings of traditional financial systems - its users can send money pseudo-anonymously while circumventing traditional banking systems. Yet, despite the fact that all financial transactions in Bitcoin are available in an openly accessible online ledger - the blockchain - not much is known about how different types of actors in the network (we call them entities) actually use Bitcoin. BitConduite offers an entity-centered view on transactions, making the data accessible to non-technical experts through a guided workflow for classification of entities according to several activity metrics. Other novelties are the possibility to cluster entities by similarity and exploration of transaction data at different scales, from large groups of entities down to a single entity and the associated transactions. Two use cases illustrate the workflow of the system and its analytic power. We report on feedback regarding the approach and the the software tool gathered during a workshop with domain experts, and we discuss the potential of the approach based on our findings.
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Preprints, Working Papers, ...
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https://hal.inria.fr/hal-02499003
Contributor : Jean-Daniel Fekete Connect in order to contact the contributor
Submitted on : Thursday, April 15, 2021 - 4:53:02 PM
Last modification on : Friday, July 2, 2021 - 11:20:45 AM
Long-term archiving on: : Friday, July 16, 2021 - 7:06:19 PM

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1912.08101.pdf
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Distributed under a Creative Commons Attribution 4.0 International License

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  • HAL Id : hal-02499003, version 1
  • ARXIV : 1912.08101

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Christoph Kinkeldey, Jean-Daniel Fekete, Tanja Blascheck, Petra Isenberg. Visualizing and Analyzing Entity Activity on the Bitcoin Network. In press. ⟨hal-02499003⟩

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