Topological Components in a Community Currency Network
Teodoro Criscione

TL;DR
This paper analyzes the structure and dynamics of a community currency network in Kenya during COVID-19 using network science, revealing the importance of cycles for currency circulation and identifying user behaviors.
Contribution
It introduces a topological categorization of network components and applies it to a real-world digital currency, providing new insights into currency circulation and user activity patterns.
Findings
Strongly connected components indicate key role of cycles in currency recirculation.
Detection of user groups potentially misusing or testing the system.
Methodology offers a quantitative tool for analyzing user behavior in currency networks.
Abstract
Transaction data from digital payment systems can be used to study economic processes in such detail that was not possible previously. Here, data from the Sarafu token network, a Community Inclusion Currency in Kenya, is analysed. During the COVID-19 emergency, Sarafu was distributed as part of a humanitarian aid project. In this work, the transactions are analysed using network science. A topological categorisation is defined to identify cyclic and acyclic components. Furthermore, temporal aspects of the circulation that takes place within these components are considered. The significant presence of different types of strongly connected components compared to randomised null models shows the importance of cycles in this economic network. Especially, indicating their key role in currency recirculation. In some acyclic components, the most significant triad suggests the presence of a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsReceptor Mechanisms and Signaling · Complex Systems and Time Series Analysis · Mathematical Dynamics and Fractals
