Complex Networks and Applications in Blockchain-Based Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 501

Special Issue Editors


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Guest Editor
Institute of Informatics, University of Zürich, 8050 Zürich, Switzerland
Interests: complex networks

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Guest Editor
UZH Blockchain Center, Department of Informatics, University of Zurich, 8050 Zurich, Switzerland
Interests: blockchain; cryptoeconomics; DeFi; blockchain analytics; complexity

Special Issue Information

Dear Colleagues,

This Special Issue is centered around the exploration of complex networks and their applications within blockchain-based networks. This includes how these networks can be understood, modeled, and utilized in various blockchain environments. It aims to cover a broad range of topics that intersect the fields of complex networks and blockchain technology. This could include the structural analysis of blockchain networks, the dynamics within these networks, and their application in areas like decentralized finance (DeFi), cryptoeconomics, and blockchain analytics. This Special Issue seeks to provide insights that will supplement the existing literature by offering new perspectives on the intersection of complex networks and blockchain technology. It aims to fill the gaps in current research by showcasing novel approaches and applications that can enhance our understanding and functionality in this rapidly evolving area. This Special Issue will build on the current body of work by offering new research and reviews that connect the theory and practice of complex networks with blockchain applications. It is expected to bridge the gaps and open new avenues for research, particularly in the analysis and application of these networks in real-world blockchain scenarios.

Dr. Jianhong Lin
Prof. Dr. Claudio J. Tessone
Guest Editors

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Keywords

  • complex networks
  • blockchain technology
  • decentralized finance (DeFi)
  • cryptoeconomics
  • blockchain analytics

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Published Papers (1 paper)

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Research

21 pages, 9799 KiB  
Article
A Complex Network Node Clustering Algorithm Based on Graph Contrastive Learning
by Chuting Zhang, Yandong Hou and Bolun Chen
Electronics 2025, 14(7), 1353; https://doi.org/10.3390/electronics14071353 - 28 Mar 2025
Viewed by 259
Abstract
With the rapid development of complex network science, exploring the characteristics of nodes and their interrelationships in networks has emerged as a topical issue which has been extensively applied in a variety of scenarios, such as market analysis, social networks, and recommendation systems. [...] Read more.
With the rapid development of complex network science, exploring the characteristics of nodes and their interrelationships in networks has emerged as a topical issue which has been extensively applied in a variety of scenarios, such as market analysis, social networks, and recommendation systems. In this paper, a complex network node clustering method based on graph contrastive learning is proposed in combination with a topology of the network and a behavioral analysis of the network nodes, which is used to deeply mine the preferences and behavioral patterns of the network nodes in order to formulate a differentiated recommendation strategy. The model automatically learns the deep feature representation of data by optimizing the distance relationship between positive and negative sample pairs, especially when dealing with complex and heterogeneous data, and is able to capture the underlying structure that is difficult to discover using traditional methods. Meanwhile, the model captures the global structure of the data by utilizing the correlation between data points and mapping the high-dimensional data to the low-dimensional space, which provides strong robustness and high clustering accuracy when dealing with non-linearly differentiable data. The research in this paper not only provides new ideas for clustering research in complex networks but also promotes the application of related methods of complex networks in multiple fields, which has important theoretical significance and practical value. Full article
(This article belongs to the Special Issue Complex Networks and Applications in Blockchain-Based Networks)
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