  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.

Human-Computer Interaction;Computers and Society