Cascade dynamics of multiplex propagation

By Damon Centola, Michael W. Macy, Victor M. Eguiluz Columbia University, Cornell University, Imedea, Spain.. 2005

306 citations recorded by the source corpus.

Random links between otherwise distant nodes can greatly facilitate the propagation of disease or information, provided contagion can be transmitted by a single active node. However, we show that when the propagation requires simultaneous exposure to multiple sources of activation, called complex propagation, the effect of random links can be just the opposite; it can make the propagation more difficult to achieve. We numerically calculate critical points for a threshold model using several classes of complex networks, including an empirical social network. We also provide an estimation of the critical values in terms of vulnerable nodes.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ddd382fdd8e5df4cf84af5dc0897bf78def4c238

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In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

Dynamics of information diffusion and its applications on complex networks (2016, background): “[186] gave numerical solution of the threshold points in various complex networks, including empirical social networks.”
Binary-state dynamics on complex networks: pair approximation and beyond (2012, unknown): “As a ﬁnal example, we consider threshold models [12–14, 69 ], which are used to model the diffusion of fads, collective”
Group formation in large social networks: membership, growth, and evolution (2006, background): “They contend that instances of successful social diffusion “typically unfol d in highly clustered networks” [ 7 ].”
The Spread of Behavior in an Online Social Network Experiment (2010, unknown): “Despite the scientific (6, 7, 10) and practical (1, 2, 11) importance of understanding the spread of behavior through social networks, an empirical test of these predictions has not been possible, because it requires the ability to independently vary the topological structure of a social network ADV”
Robustness and resilience of complex networks (2024, background): “The condition for the emergence of global cascades and estimates for their size have been successfully generalized to networks with topological correlations 173–177 and to temporal 178,179 and multiplex networks 180 .”
The Simple Rules of Social Contagion (2013, unknown): “A number of explanations have been oﬀered for this aberration, including complex contagion [8, 14, 32].”
The "Majority Illusion" in Social Networks (2015, unknown): “Researchers use the threshold model to describe the spread of social contagions in networks [10, 17, 32].”
Social Influence, Binary Decisions and Collective Dynamics (2008, background): “Heuristic models, which dominate the diffusion of innovations and collective action literature (Anderson and May 1991; Centola et al. 2007; Glaeser et al. 1996; Granovetter 1978; Watts 2002), posit some usually simple rule according to which individuals will ‘adopt’ some practice (which can be vario”