Article
Physics, Fluids & Plasmas
Yilun Shang
Summary: Percolation models are important for understanding complex systems, but little is known about how non-topological features influence these models. In this paper, a feature-enriched core percolation framework is introduced to analyze the features and structure of the cores. The study finds continuous and discrete percolation transitions at critical correlation levels.
Article
Physics, Multidisciplinary
Kexian Zheng, Ying Liu, Yang Wang, Wei Wang
Summary: This study investigates the robustness of multiplex networks with interdependent and interconnected links under different inter-layer coupling strengths, revealing the close relationship between system robustness and inter-network dependencies.
Article
Mathematics, Applied
Mingze Qi, Peng Chen, Jun Wu, Yuan Liang, Xiaojun Duan
Summary: This paper focuses on studying the robustness measures for different types of multiplex networks. It generalizes the natural connectivity calculated from the graph spectrum to evaluate the robustness of multiplex networks consisting of connective or dependent layers. The experiments conducted on model and real multiplex networks demonstrate a close correlation between the robustness of such networks and the natural connectivity of aggregated networks or intersections between layers. These findings contribute to enhancing the design and protection of coupled complex systems.
Article
Mathematics, Interdisciplinary Applications
Yuan Liang, Mingze Qi, Huangpeng Qizi, Xiaojun Duan
Summary: This study proposes a percolation framework to investigate the properties of interlayer feature-correlated multiplex networks. The results show that the degree-degree correlation of the network is controlled by both the correlation between degrees and features, and the correlation between the features of different layers. Additionally, the network structure is randomized when there are repeating features.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Multidisciplinary Sciences
R. A. da Costa, G. J. Baxter, S. N. Dorogovtsev, J. F. F. Mendes
Summary: A novel discontinuous phase transition is observed in weak multiplex percolation, focusing on stability of networks with three or more layers and the effects of node or edge removal on network collapse or recovery.
SCIENTIFIC REPORTS
(2022)
Article
Physics, Fluids & Plasmas
Hanlin Sun, Ginestra Bianconi
Summary: This study establishes a general framework for assessing hypergraph robustness and characterizes the critical properties of simple and higher-order percolation processes. The research shows that the ensemble of multiplex hypergraphs can be mapped to an ensemble of multiplex bipartite networks under certain conditions. Additionally, it reveals the relationships between higher-order percolation processes, interdependent percolation of multiplex networks, and K-core percolation.
Article
Mathematics, Interdisciplinary Applications
G. J. Baxter, R. A. da Costa, S. N. Dorogovtsev, J. F. F. Mendes
Summary: We solve the weak percolation problem for multiplex networks with overlapping edges. Our theory shows that in two layers, any (nonzero) concentration of overlaps drives the weak percolation transition to the ordinary percolation universality class. In three layers, the phase diagram of the problem contains two lines - of a continuous phase transition and of a discontinuous one - connected in various ways depending on how the layers overlap.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Condensed Matter
Jihui Han, Shaoyang Tang, Yuefeng Shi, Longfeng Zhao, Jianyong Li
Summary: Network dismantling is crucial in identifying the minimal set of nodes whose removal disrupts the network into subcomponents. An efficient dismantling algorithm based on network decycling is proposed for multiplex networks under layer node-based attack. Experimental results show the algorithm outperforms existing ones, and demonstrate how interlayer degree correlation affects the robustness of multiplex networks.
EUROPEAN PHYSICAL JOURNAL B
(2021)
Article
Multidisciplinary Sciences
F. Musciotto, S. Micciche
Summary: Network dismantling is a significant research field in network science, which focuses on prioritizing the removal of nodes that connect different network communities. The study shows that the dismantling performances are robust and not dependent on specific algorithms, allowing for the identification of multiple strategies with comparable effectiveness.
SCIENTIFIC REPORTS
(2023)
Article
Physics, Fluids & Plasmas
Daniel Kaiser, Siddharth Patwardhan, Filippo Radicchi
Summary: A multiplex is a collection of network layers, each representing a specific type of edges. However, observing multiplex data directly can be difficult due to various factors. This study proposes an algorithm to reconstruct the hidden multiplex structure of an aggregated network from partial information by leveraging layerwise community structure. The algorithm has a linear computational time and is evaluated on both synthetic and real-world multiplex networks.
Article
Physics, Multidisciplinary
Hillel Sanhedrai, Shlomo Havlin
Summary: Epidemics on complex networks have been extensively studied in recent years, primarily due to past pandemic events. Real contact networks are usually dynamic, so much effort has been dedicated to exploring epidemics on evolving networks. In this study, we propose and analyze a model for evolving networks based on varying degrees. We find the epidemic threshold and the probability of disease spread using analytical methods and confirm our results with numerical simulations. Our findings show that the impact of the rewiring rate r differs qualitatively for networks with different degree distributions. We also discover that the extreme vulnerability of static scale-free networks disappears when the networks evolve fully, suggesting the importance of network dynamics in epidemic spreading. Additionally, we determine the epidemic threshold for a general distribution of recovery time.
NEW JOURNAL OF PHYSICS
(2022)
Review
Mathematics, Interdisciplinary Applications
Miguel-Angel Martinez Cruz, Julian Patino Ortiz, Miguel Patino Ortiz, Alexander Balankin
Summary: The purpose of this survey is two-fold: first, to survey the studies of percolation on fractal networks in order to assess the current state of the art and highlight the main findings and gaps in understanding; second, to provide guidelines for future research by focusing on the effects of fractal attributes on percolation in self-similar networks and outlining challenging questions.
FRACTAL AND FRACTIONAL
(2023)
Article
Multidisciplinary Sciences
Gaogao Dong, Fan Wang, Louis M. Shekhtman, Michael M. Danziger, Jingfang Fan, Ruijin Du, Jianguo Liu, Lixin Tian, H. Eugene Stanley, Shlomo Havlin
Summary: The research indicates that in modular networks, an optimal fraction of interconnected nodes exists where the system becomes optimally resilient and is able to withstand more damage. Although the exact location of the optimal fraction varies based on the coupling patterns, there exists such an optimal point for all coupling patterns.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Computer Science, Artificial Intelligence
Chunying Li, Xiaojiao Guo, Weijie Lin, Zhikang Tang, Jinli Cao, Yanchun Zhang
Summary: Multiplex networks are useful for modeling complex systems, such as academic social networks. Composite community structures can reveal meaningful grouping patterns in multiplex networks. The proposed CDMA algorithm, based on motif awareness, reduces information loss during the aggregation of multiplex networks and improves the quality of community detection.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Physics, Fluids & Plasmas
Steve J. Kongni, Venceslas Nguefoue, Thierry Njougouo, Patrick Louodop, Fernando Fagundes Ferreira, Robert Tchitnga, Hilda A. Cerdeira
Summary: This study analyzes the dynamics of bidirectionally coupled swarmalators subject to attractive and repulsive couplings. The probability of connections between elements in different layers strongly depends on the defined vision range rc, leading to different patterns in both layers. The study discovers interlayer static sync and proves its stability. The study also observes first-order and second-order transitions under different conditions.
Article
Physics, Condensed Matter
Dario Mazzilli, Filippo Radicchi
Summary: This study develops a combinatorial framework for stochastic spreading models defined on complex network topologies, resulting in more accurate predictions of diffusion and theoretical properties of inference problems.
EUROPEAN PHYSICAL JOURNAL B
(2021)
Article
Geosciences, Multidisciplinary
Filipi N. Silva, Didier A. Vega-Oliveros, Xiaoran Yan, Alessandro Flammini, Filippo Menczer, Filippo Radicchi, Ben Kravitz, Santo Fortunato
Summary: This study introduces a novel method using Granger causality to study climate system teleconnections, which can recover known seasonal precipitation responses and identify candidates for unexplored teleconnection responses.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Multidisciplinary Sciences
Weiwei Gu, Aditya Tandon, Yong-Yeol Ahn, Filippo Radicchi
Summary: Network embedding is a machine learning technique that encodes network structure in vector spaces, choosing an appropriate embedding dimension is challenging but important. The proposed principled method can effectively select embedding dimensions in real-world networks.
NATURE COMMUNICATIONS
(2021)
Article
Multidisciplinary Sciences
Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli, Filippo Radicchi
Summary: This study analyzes time-stamped events from several online social media platforms over a period of more than ten years and reveals the universality and criticality of information propagation in social media. The propagation of information can occur through simple or complex contagion processes, with the complexity of the process being correlated with the semantic content of the information being propagated.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Thomas Parmer, Luis M. Rocha, Filippo Radicchi
Summary: This study develops a method to solve the optimization problem of finding minimal sets of nodes that can drive the dynamics of Boolean networks towards desired long-term behaviors. The method is inspired by the problem of influence maximization in social networks and has been validated through experiments.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Hanlin Sun, Filippo Radicchi, Juergen Kurths, Ginestra Bianconi
Summary: The authors study percolation in networks with higher-order interactions and propose a triadic percolation model. They find that the connectivity of the network changes in time and that the order parameter undergoes period doubling and chaos. They develop a theory for triadic percolation on random graphs and find similar phenomena in real network topologies. These findings change our understanding of percolation and have important implications for studying dynamic and complex systems such as neural and climate networks.
NATURE COMMUNICATIONS
(2023)
Article
Physics, Fluids & Plasmas
Daniel Kaiser, Siddharth Patwardhan, Filippo Radicchi
Summary: A multiplex is a collection of network layers, each representing a specific type of edges. However, observing multiplex data directly can be difficult due to various factors. This study proposes an algorithm to reconstruct the hidden multiplex structure of an aggregated network from partial information by leveraging layerwise community structure. The algorithm has a linear computational time and is evaluated on both synthetic and real-world multiplex networks.
Article
Information Science & Library Science
Sirag Erkol, Satyaki Sikdar, Filippo Radicchi, Santo Fortunato
Summary: This article examines the scientific portfolios of Nobel Prize laureates and finds that consistently producing high-quality work is the most successful path.
QUANTITATIVE SCIENCE STUDIES
(2023)
Article
Physics, Multidisciplinary
Saeed Osat, Fragkiskos Papadopoulos, Andreia Sofia Teixeira, Filippo Radicchi
Summary: Optimal percolation refers to the determination of the minimum-cost strategy for destroying extensive connected components in a network. This is crucial for designing optimal disease containment strategies based on immunization or social distancing. The study shows that network representations in geometric space can effectively solve various network dismantling problems. The proposed approach performs well in both Euclidean and hyperbolic network embeddings, comparable to, or even better than, existing dismantling algorithms.
PHYSICAL REVIEW RESEARCH
(2023)
Article
Physics, Fluids & Plasmas
Daniele Notarmuzi, Alessandro Flammini, Claudio Castellano, Filippo Radicchi
Summary: We investigate the temporal statistics of avalanche dynamics in the SIS model on finite random networks at criticality. Our numerical simulations on annealed topologies reveal three distinct dynamical regimes in the survival probability. We find that the crossover timescales separating these regimes scale differently for homogeneous and heterogeneous networks. The qualitative understanding of the phenomenology is based on known features of SIS dynamics, while a fully quantitative approach using Langevin theory reproduces the results only for homogeneous networks.
Article
Physics, Fluids & Plasmas
Sirag Erkol, Dario Mazzilli, Filippo Radicchi
Summary: This study investigates influence maximization on temporal networks and finds that the greedy strategy provides effective approximation solutions for this problem in both real and synthetic networks. The paper compares the results of the greedy strategy with the exact solutions obtained through brute-force search.
Article
Physics, Fluids & Plasmas
Yi-Jiao Zhang, Kai-Cheng Yang, Filippo Radicchi
Summary: This research systematically compares 11 different graph embedding methods, including embedding methods in hyperbolic and Euclidean metric spaces as well as nonmetric community-based embedding methods. The results show that some Euclidean embedding methods excel in greedy routing, while community-based and hyperbolic embedding methods perform superior in link prediction compared to Euclidean-space-based approaches.
Article
Mathematics, Interdisciplinary Applications
Sirag Erkol, Filippo Radicchi
Summary: The study analyzes the performance data of coaches from European soccer clubs and American basketball teams throughout history, identifying the top coaches historically and ranking them by different time periods. The research also provides a website for readers to access the complete analysis results.
JOURNAL OF COMPLEX NETWORKS
(2021)
Article
Physics, Fluids & Plasmas
Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli, Filippo Radicchi
Summary: This study investigates the impact of different temporal resolutions on the properties of activity patterns, revealing that the same process can lead to different distributions of burst sizes and durations. The competition between 1D percolation and branching process universality classes results in distinct outcomes, with hybrid scaling observed in a wide region of the diagram.
Article
Physics, Fluids & Plasmas
Aditya Tandon, Aiiad Albeshri, Vijey Thayananthan, Wadee Alhalabi, Filippo Radicchi, Santo Fortunato
Summary: This paper investigates the application of graph embedding techniques for community detection and compares their performance with traditional algorithms. The study finds that with suitable parameter selection, the performance of graph embedding techniques is comparable to traditional algorithms. However, due to parameter sets varying with benchmark graph features, embedding techniques do not surpass community detection algorithms.
