mlsanityData to 7 Oct 2026

The structure and dynamics of multilayer networks

arXiv 1407.0742 ↗First posted 2 Jul 2014physics.soc-ph cs.SI nlin.AOcited by 51

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Abstract (arXiv)

In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.

Key facts. Cited by 51 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jul 2014.

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Citing papers per year: 2021: 8; 2022: 9; 2023: 11; 2024: 10; 2025: 3; 2026: 10.

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  1. 2023A critical look at the evaluation of GNNs under heterophily: Are we really making progress?cited by 332
  2. 2024GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Datacited by 20
  3. 2021Machine learning dismantling and early-warning signals of disintegration in complex systemscited by 14
  4. 2024AI-enhanced Collective Intelligencecited by 10
  5. 2021Time Series Analysis via Network Science: Concepts and Algorithmscited by 8
  6. 2021Graph-Based Similarity of Neural Network Representationscited by 7
  7. 2022Koopman-based spectral clustering of directed and time-evolving graphscited by 6
  8. 2021Cognitive network science for understanding online social cognitions: A brief reviewcited by 5
  9. 2022Network-level Safety Metrics for Overall Traffic Safety Assessment: A Case Studycited by 5
  10. 2021mGNN: Generalizing the Graph Neural Networks to the Multilayer Casecited by 4
  11. 2022Ranking with multiple types of pairwise comparisonscited by 4
  12. 2022Emotion Analysis using Multi-Layered Networks for Graphical Representation of Tweetscited by 3
38 more
  1. 2023DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveformscited by 3
  2. 2024Community detection by spectral methods in multi-layer networkscited by 3
  3. 2021Universal Multilayer Network Exploration by Random Walk with Restartcited by 2
  4. 2022Quantitative Discourse Cohesion Analysis of Scientific Scholarly Texts using Multilayer Networkscited by 2
  5. 2023Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safetycited by 2
  6. 2023Zoo Guide to Network Embeddingcited by 2
  7. 2023Privacy-Preserving Community Detection for Locally Distributed Multiple Networkscited by 2
  8. 2026Emergence of Fragility in LLM-based Social Networks: the Case of Moltbookcited by 2
  9. 2021Propagation on Multi-relational Graphs for Node Regressioncited by 1
  10. 2022Efficient multi-relational network representation using primescited by 1
  11. 2023A Network Science perspective of Graph Convolutional Networks: A surveycited by 1
  12. 2023Astrocytes as a mechanism for meta-plasticity and contextually-guided network functioncited by 1
  13. 2024Enhancing Graph Neural Networks in Large-scale Traffic Incident Analysis with Concurrency Hypothesiscited by 1
  14. 2024Geographical Information Alignment Boosts Traffic Analysis via Transpose Cross-attentioncited by 1
  15. 2026A Dynamic Atlas of Persian Poetic Symbolism: Families, Fields, and the Historical Rewiring of Meaningcited by 1
  16. 2026Cluster Attention for Graph Machine Learningcited by 1
  17. 2026The role of System 1 and System 2 semantic memory structure in human and LLM biasescited by 1
  18. 2021Inference of time-ordered multibody interactionscited by 0
  19. 2022MultiSAGE: a multiplex embedding algorithm for inter-layer link predictioncited by 0
  20. 2022Factorized Fusion Shrinkage for Dynamic Relational Datacited by 0
  21. 2022Cognitive modelling with multilayer networks: Insights, advancements and future challengescited by 0
  22. 2023Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descentcited by 0
  23. 2023The Structure and Dynamics of Knowledge Graphs, with Superficialitycited by 0
  24. 2023XFlow: Benchmarking Flow Behaviors over Graphscited by 0
  25. 2023Unsupervised Learning via Network-Aware Embeddingscited by 0
  26. 2024MPXGAT: An Attention based Deep Learning Model for Multiplex Graphs Embeddingcited by 0
  27. 2024Estimating mixed memberships in multi-layer networkscited by 0
  28. 2024Efficient PAC Learnability of Dynamical Systems Over Multilayer Networkscited by 0
  29. 2024From Primes to Paths: Enabling Fast Multi-Relational Graph Analysiscited by 0
  30. 2024Master Stability Functions in Complex Networkscited by 0
  31. 2025MSGCN: Multiplex Spatial Graph Convolution Network for Interlayer Link Weight Predictioncited by 0
  32. 2025Identifying Group Anchors in Real-World Group Interactions Under Label Scarcitycited by 0
  33. 2025Learning Multi-Order Block Structure in Higher-Order Networkscited by 0
  34. 2026Temporal Complexity and Self-Organization in an Exponential Dense Associative Memory Modelcited by 0
  35. 2026Embedding Learning on Multiplex Networks for Link Predictioncited by 0
  36. 2026Large language models for spreading dynamics in complex systemscited by 0
  37. 2026Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networkscited by 0
  38. 2026T-GINEE: A Tensor-Based Multilayer Graph Representation Learningcited by 0

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