BitConduite: Exploratory Visual Analysis of Entity Activity on the Bitcoin Network

Abstract

We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e. by individuals, companies or other groups actively using Bitcoin. BitConduite makes Bitcoin data accessible to non-technical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts.

Publication
IEEE Computer Graphics and Applications

Notes

Visual Analytics Big Data Machine Learning Workshop