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BitConduite: Exploratory Visual Analysis of Entity Activity on the Bitcoin Network.
IEEE Computer Graphics and Applications
|April 13, 2021
Summary
BitConduite offers a visual analytics tool for exploring Bitcoin financial activity. It helps non-experts understand transactions aggregated by entities, aiding in analysis and pattern identification.
Area of Science:
- Computer Science
- Data Visualization
- Financial Technology
Background:
- The Bitcoin network generates vast amounts of transaction data.
- Analyzing this data is challenging for non-technical users.
- Existing tools often lack user-friendly interfaces for exploring entity-based financial activity.
Purpose of the Study:
- To introduce BitConduite, a visual analytics approach for Bitcoin financial activity.
- To enable non-technical experts to explore and analyze Bitcoin transactions aggregated by entities.
- To facilitate the identification of patterns and clusters within Bitcoin transaction data.
Main Methods:
- Developed a visual analytics approach named BitConduite.
- Implemented a guided workflow for analyzing entities based on activity metrics.
- Enabled analysis at various scales, from single entities to large groups.
- Incorporated entity clustering for identifying similar activities and temporal patterns.
Main Results:
- BitConduite provides an accessible interface for Bitcoin data exploration.
- The system allows for detailed analysis of financial activity aggregated by entities.
- Users can identify and explore groups of entities with similar transaction patterns.
- Domain expert feedback was collected to assess the approach's value.
Conclusions:
- BitConduite enhances the accessibility of Bitcoin network data for non-technical users.
- The visual analytics approach supports explorative analysis of financial activities and entity behaviors.
- BitConduite facilitates the discovery of transaction patterns and clusters within the Bitcoin ecosystem.
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