Spreading Dynamics in Complex Networks
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: 15 April 2025 | Viewed by 157
Special Issue Editor
Special Issue Information
Dear Colleagues,
Complex networks have emerged as a powerful tool which has helped the research community understand how simple interactions can evolve into intricate large-scale systems with unforeseen properties. These networks provide the substrate that facilitates dynamical processes. The network topology can be critical to predicting the evolution of these processes and multiple new phenomena have been reported, compared to fully mixed models which ignore the network structure. This approach has enabled the study of numerous spreading phenomena with real-world implications and universally applicable principles. Universal features have been found in diverse systems, such as in the study of infectious diseases, computer viruses, information and misinformation, spreading belief propagation, and others. This Special Issue seeks to deepen our understanding of any type of spreading processes through networks from a holistic perspective, ranging from abstract models to analysis of real-world situations. Papers reporting theoretical results, data analysis, or computational modeling, as well as methodology papers are all welcome. Of particular interest is the potential of artificial intelligence models to transform our ability to analyze spreading processes.
Prof. Dr. Lazaros Gallos
Guest Editor
Manuscript Submission Information
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Keywords
- epidemic spreading
- network science
- network dynamics
- information spreading
- social network analysis
- computational modeling
- infectious disease modeling
- percolation theory
- machine learning in complex networks
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
1. Diaoulé Diallo, German Aerospace Center
2. Zhijian Zhang, Kunming University of Science and Technology
