The physics of spreading processes in multilayer networks
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Abstract (arXiv)
The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent "multilayer" approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2016.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2021Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networkscited by 18
- 2021Machine learning dismantling and early-warning signals of disintegration in complex systemscited by 14
- 2021Survey of Generative Methods for Social Media Analysiscited by 1
- 2026Large language models for spreading dynamics in complex systemscited by 0
- 2026Large language models for spreading dynamics in complex systems8 Feb 2026
- 2021Survey of Generative Methods for Social Media Analysis13 Dec 2021
- 2021Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks21 Jul 2021
- 2021Machine learning dismantling and early-warning signals of disintegration in complex systems7 Jan 2021