Composite Effective Degree Markov Chain for Epidemic Dynamics on Higher-Order Networks DOI
Jiaxing Chen, Meiling Feng, Dawei Zhao

et al.

IEEE Transactions on Systems Man and Cybernetics Systems, Journal Year: 2023, Volume and Issue: 53(12), P. 7415 - 7426

Published: Aug. 14, 2023

Epidemiological models based on traditional networks have made important contributions to the analysis and control of malware, disease, rumor propagation. However, higher-order are becoming a more effective means for modeling epidemic spread characterizing topology group interactions. In this article, we propose composite degree Markov chain approach (CEDMA) describe discrete-time dynamics networks. approach, nodes classified according number neighbors hyperedges in different states characterize By comparing with microscopic CEDMA can better match numerical simulations Monte Carlo accurately capture discontinuous phase transitions bistability phenomena caused by particular, theoretical solution well predict critical point at continuous transition corroborate existence susceptible–infectious–susceptible (SIS) process. Moreover, be further extended depict susceptible–infectious–recovered (SIR) process

Language: Английский

The physics of higher-order interactions in complex systems DOI
Federico Battiston, Enrico Amico, Alain Barrat

et al.

Nature Physics, Journal Year: 2021, Volume and Issue: 17(10), P. 1093 - 1098

Published: Oct. 1, 2021

Language: Английский

Citations

550
Dynamics on higher-order networks: a review DOI Creative Commons
Soumen Majhi, Matjaž Perc, Dibakar Ghosh

et al.

Journal of The Royal Society Interface, Journal Year: 2022, Volume and Issue: 19(188)

Published: March 1, 2022

Network science has evolved into an indispensable platform for studying complex systems. But recent research identified limits of classical networks, where links connect pairs nodes, to comprehensively describe group interactions. Higher-order a link can more than two have therefore emerged as new frontier in network science. Since interactions are common social, biological and technological systems, higher-order networks recently led important discoveries across many fields research. Here, we review these works, focusing particular on the novel aspects dynamics that emerges networks. We cover variety dynamical processes thus far been studied, including different synchronization phenomena, contagion processes, evolution cooperation consensus formation. also outline open challenges promising directions future

Language: Английский

Citations

332
The structure and dynamics of networks with higher order interactions DOI
Stefano Boccaletti, Pietro De Lellis, Charo I. del Genio

et al.

Physics Reports, Journal Year: 2023, Volume and Issue: 1018, P. 1 - 64

Published: May 1, 2023

Language: Английский

Citations

152
Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes DOI Creative Commons
Yuanzhao Zhang, Maxime Lucas, Federico Battiston

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: March 23, 2023

Abstract Higher-order networks have emerged as a powerful framework to model complex systems and their collective behavior. Going beyond pairwise interactions, they encode structured relations among arbitrary numbers of units through representations such simplicial complexes hypergraphs. So far, the choice between hypergraphs has often been motivated by technical convenience. Here, using synchronization an example, we demonstrate that effects higher-order interactions are highly representation-dependent. In particular, typically enhance in but opposite effect complexes. We provide theoretical insight linking synchronizability different hypergraph structures (generalized) degree heterogeneity cross-order correlation, which turn influence wide range dynamical processes from contagion diffusion. Our findings reveal hidden impact on dynamics, highlighting importance choosing appropriate when studying with nonpairwise interactions.

Language: Английский

Citations

111
Higher-order motif analysis in hypergraphs DOI Creative Commons
Quintino Francesco Lotito, Federico Musciotto, Alberto Montresor

et al.

Communications Physics, Journal Year: 2022, Volume and Issue: 5(1)

Published: April 5, 2022

Abstract A deluge of new data on real-world networks suggests that interactions among system units are not limited to pairs, but often involve a higher number nodes. To properly encode higher-order interactions, richer mathematical frameworks such as hypergraphs needed, where hyperedges describe an arbitrary Here we systematically investigate motifs, defined small connected subgraphs in which vertices may be linked by any order, and propose efficient algorithm extract complete motif profiles from empirical data. We identify different families hypergraphs, characterized distinct connectivity patterns at the local scale. also set measures study nested structure provide evidences structural reinforcement, mechanism associates strengths for nodes interact more pairwise level. Our work highlights informative power providing principled way fingerprints network microscale.

Language: Английский

Citations

91
Epidemic spreading on higher-order networks DOI
Wei Wang, Yanyi Nie, Wenyao Li

et al.

Physics Reports, Journal Year: 2024, Volume and Issue: 1056, P. 1 - 70

Published: Jan. 19, 2024

Language: Английский

Citations

69
The SIQRS Propagation Model With Quarantine on Simplicial Complexes DOI
Jiaxing Chen, Chengyi Xia, Matjaž Perc

et al.

IEEE Transactions on Computational Social Systems, Journal Year: 2024, Volume and Issue: 11(3), P. 4267 - 4278

Published: Feb. 2, 2024

Simplicial complexes successfully resolve the limitation of social networks to describe spread infectious diseases in group interactions. However, effects quarantines context interactions remain largely unaddressed. In this article, we therefore propose a susceptible-infectious-quarantine- recovered-susceptible (SIQRS) model with and study its evolution on simplicial complexes. model, fraction infected individuals is subject quarantine, but leaving quarantine may still be contagious. Using mean-field (MF) methods, derive propagation threshold steady state infection densities as well conditions for their stability. Numerical simulations moreover show that longer times higher ratios tend disrupt discontinuous phase transition bistable phenomena are commonly due Additionally, when epidemic outbreaks recurrent, although measures can reduce peak first wave delay onset future waves, they also lead an increase subsequent densities. This highlights need prepare sufficient resources deal periodic infections after initial over.

Language: Английский

Citations

21
Contagion dynamics on higher-order networks DOI
Guilherme Ferraz de Arruda, Alberto Aleta, Yamir Moreno

et al.

Nature Reviews Physics, Journal Year: 2024, Volume and Issue: 6(8), P. 468 - 482

Published: July 5, 2024

Language: Английский

Citations

18
Group interactions modulate critical mass dynamics in social convention DOI Creative Commons
Iacopo Iacopini, Giovanni Petri, Andrea Baronchelli

et al.

Communications Physics, Journal Year: 2022, Volume and Issue: 5(1)

Published: March 18, 2022

Abstract How can minorities of individuals overturn social conventions? The theory critical mass states that when a committed minority reaches size, cascade behavioural changes occur, overturning apparently stable norms. Evidence comes from theoretical and empirical studies in which very different sizes, including extremely small ones, manage to bring system its tipping point. Here, we explore this diversity scenarios by introducing group interactions as crucial element realism into model for convention. We find the necessary trigger behaviour change be if have limited propensity their views. Moreover, ability existing norms depends complex way on size. Our findings reconcile sizes found previous investigations unveil role groups such processes. This further highlights importance emerging field higher-order networks, beyond pairwise interactions.

Language: Английский

Citations

42
Community detection in large hypergraphs DOI Creative Commons
Nicolò Ruggeri, Martina Contisciani, Federico Battiston

et al.

Science Advances, Journal Year: 2023, Volume and Issue: 9(28)

Published: July 12, 2023

Hypergraphs, describing networks where interactions take place among any number of units, are a natural tool to model many real-world social and biological systems. Here, we propose principled framework the organization higher-order data. Our approach recovers community structure with accuracy exceeding that currently available state-of-the-art algorithms, as tested in synthetic benchmarks both hard overlapping ground-truth partitions. is flexible allows capturing assortative disassortative structures. Moreover, our method scales orders magnitude faster than competing making it suitable for analysis very large hypergraphs, containing millions nodes thousands nodes. work constitutes practical general hypergraph analysis, broadening understanding

Language: Английский

Citations

35