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10.1063/5.0020034 http://scihub22266oqcxt.onion/10.1063/5.0020034 33138447!7585450!33138447     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Chaos 2020 ; 30 (10): 103117 Nephropedia Template TP {{tp|p=33138447|t=2020. The effect of heterogeneity on hypergraph contagion models |pdf=|usr=}}{{33138447}} gab.com Text The effect of heterogeneity on hypergraph contagion models JO: Chaos http://www.kidney.de/pget.php?&tw=1&pmid=33138447 #FOAvip The dynamics of network social contagion processes such as opinion formation and epidemic spreading are often mediated by interactions between multiple nodes. Previous results have shown that these higher-order interactions can profoundly modify the dynamics of contagion processes, resulting in bistability, hysteresis, and explosive transitions. In this paper, we present and analyze a hyperdegree-based mean-field description of the dynamics of the susceptible-infected-susceptible model on hypergraphs, i.e., networks with higher-order interactions, and illustrate its applicability with the example of a hypergraph where contagion is mediated by both links (pairwise interactions) and triangles (three-way interactions). We consider various models for the organization of link and triangle structures and different mechanisms of higher-order contagion and healing. We find that explosive transitions can be suppressed by heterogeneity in the link degree distribution when links and triangles are chosen independently or when link and triangle connections are positively correlated when compared to the uncorrelated case. We verify these results with microscopic simulations of the contagion process and with analytic predictions derived from the mean-field model. Our results show that the structure of higher-order interactions can have important effects on contagion processes on hypergraphs. Twit Text FOAVip The effect of heterogeneity on hypergraph contagion models ????Chaos http://www.kidney.de/pget.php?&tw=1&pmid=33138447 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33138447 #FOAvip English Wikipedia <ref>{{Cite pmid|33138447}}</ref> The effect of heterogeneity on hypergraph contagion models #MMPMID33138447 Landry NW; Restrepo JG Chaos 2020[Oct]; 30 (10): 103117 PMID33138447show ga The dynamics of network social contagion processes such as opinion formation and epidemic spreading are often mediated by interactions between multiple nodes. Previous results have shown that these higher-order interactions can profoundly modify the dynamics of contagion processes, resulting in bistability, hysteresis, and explosive transitions. In this paper, we present and analyze a hyperdegree-based mean-field description of the dynamics of the susceptible-infected-susceptible model on hypergraphs, i.e., networks with higher-order interactions, and illustrate its applicability with the example of a hypergraph where contagion is mediated by both links (pairwise interactions) and triangles (three-way interactions). We consider various models for the organization of link and triangle structures and different mechanisms of higher-order contagion and healing. We find that explosive transitions can be suppressed by heterogeneity in the link degree distribution when links and triangles are chosen independently or when link and triangle connections are positively correlated when compared to the uncorrelated case. We verify these results with microscopic simulations of the contagion process and with analytic predictions derived from the mean-field model. Our results show that the structure of higher-order interactions can have important effects on contagion processes on hypergraphs. |*Epidemics[MESH] |*Group Processes[MESH] |*Mass Behavior[MESH] |*Models, Biological[MESH] |*Social Networking[MESH] |Humans[MESH]The effect of heterogeneity on hypergraph contagion models (epmc).pdf DeepDyve Pubget Overpricing