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 (http://www.
In the article "Visualizing Dynamic Bitcoin Transaction Patterns (http://online.
"This is a bold attempt at a comprehensive visualization of bitcoin transactions for a lay audience," says Big Data Editor-in-Chief Vasant Dhar, Professor at the Stern School of Business and the Center for Data Science at New York University, "but should also be of great interest to regulators and bankers who are trying to make sense of blockchain and related methods that can work without a central trusted intermediary. There is a lot of confusion about these emerging methods and a real need for articles that cut through the clutter and explain them in simple terms. Visualization is a key to understanding them."
About the Journal
Big Data (http://www.
About the Publisher
Mary Ann Liebert, Inc., publishers (http://www.