Real-time visualization tool reveals behavioral patterns in Bitcoin transactions Mary Ann Liebert, Inc./Genetic …


IMAGE: Big Data, published quarterly online with open access options and in print, facilitates and supports the efforts of researchers, analysts, statisticians, business leaders, and policymakers to improve operations, profitability, and…
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Credit: ©Mary Ann Liebert, Inc., publishers

New Rochelle, July 5, 2016–A novel visualization method for exploring dynamic patterns in real-time Bitcoin transactional data can zoom in on individual transactions in large blocks of data and also detect meaningful associations between large numbers of transactions and recurring patterns such as money laundering. The information and insights made possible by this top-down visualization of Bitcoin cryptocurrency transactions are described in an article in Big Data, the highly innovative, peer-reviewed journal from Mary Ann Liebert, Inc., publishers ( The article is available free for download on the Big Data ( website.

In the article “Visualizing Dynamic Bitcoin Transaction Patterns (,” Dan McGinn, David Birch, David Akroyd, Miguel Molina-Solana, Yike Guo, and William Knottenbelt, Imperial College London, U.K., compare their visualization approach to previous bottom-up methods,

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