EPJ Data Science Highlight - Identifying inequality in the velocity of cryptocurrency

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Published on 04 April 2025

Analysis of a new framework for tracking cryptocurrency velocity reveals deep inequalities, driven not just by wealth but by economic behaviours of individuals

The ‘velocity of money’ describes the number of times a unit of currency is used to purchase goods or services within a given time period – or in other words, the number of times that money is changing hands. The quantity is a key indicator of the behaviours of economies as a whole – but today, researchers are still uncertain as to how the concept translates to the fast-growing field of cryptocurrency.

Through new analysis published in EPJ Data Science, Francesco Maria De Collibus and colleagues at the University of Zurich investigate a newly developed framework for measuring the velocity of cryptocurrencies – named ‘MicroVelocity’. Their analysis reveals that many of the same inequalities in wealth distribution found in the economy as a whole are also reflected in MicroVelocity.

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EPJ Data Science Highlight - Mapping the cross-generational impact of musical sampling

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Published on 14 February 2025

Advanced network analysis reveals how musical sampling has driven the evolution of contemporary music, and enabled the revival of dormant musical styles to across generations.

Sampling has helped musicians to craft a rich and diverse musical landscape, and has bridged the gap between different generations of creators. By acting as ‘cultural genes’ which are passed down and incorporated into new compositions, samples can fundamentally shape the genre, mood, and identity of contemporary music: posing questions about how sampling has influenced the evolution of popular music over time.

Through new analysis published in EPJ Data Science, Dongju Park and Juyong Park at the Korea Advanced Institute of Science and Technology provide new insights into how sampling has driven the constant development of music, revived styles dormant for generations, and fostered connections between generations of musicians. Their work demonstrates the complex nature of musical evolution, and how it can be understood using the powerful mathematics of network frameworks.

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EPJ Data Science appoints Prof. David Garcia as co-Editor-in-Chief

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Published on 14 January 2025

EPJ is pleased to announce that Prof. David Garcia has been appointed as co-Editor-in-Chief of EPJ Data Science, effective January 2025. He will be responsible for overseeing the editorial process and development of the journal, working closely with Dr Yelena Mejova, who continues to serve as co-Editor-in-Chief.

David Garcia is Professor of Social and Behavioral Data Science at the Center for Data and Methods in the Department of Politics and Public Administration at the University of Konstanz. He is also associate faculty at the Complexity Science Hub Vienna and visiting professor at the Barcelona Supercomputing Center. He works on the analysis of human behavior with digital trace data and computational models. He has specialized in the analysis of collective emotions and polarization with methods from Data Science and responsible Artificial Intelligence.

He has co-authored more than 100 articles in conferences and journals in Computer Science, Physics, Political Science, and Psychology. He served as program co-chair of the 2023 International School and Conference on Network Science and is serving as program co-chair of the 2025 International Conference on Computational Social Science.