A simple model of global cascades on random networks

By Duncan J. Watts. Proceedings of the National Academy of Sciences of the United States of America, 2002

2,565 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/90468dc37b06638b1358e2764084bd6822565f6d

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Citations in the corpus

The structure and dynamics of multilayer networks (2014, background): “[200], or by novel cascade processes [201].”
Web-based experiments for the study of collective social dynamics in cultural markets (2009, background): “…(Arthur, 1994; Axelrod, 1997; Banerjee, 1992; Bikhchandani, Hirshleifer, & Welch, 1992; Goldstone, Ashpole, & Roberts, 2005; Macy & Willer, 2002; Watts, 2002), but these approaches are invariably subject to the critique that they are based on overly simplistic representations of human behavior…”
Vital nodes identification in complex networks (2016, background): “Fortunately, both the independent cascade model and SIR model are equivalent to a bond percolation [144, 242, 243, 244, 245] (the connections between computer science and physical models were largely ignored in the literature, for example, the well-known bootstrap percolation model [246, 247] can be”
Majority bootstrap percolation on the random graph G(n,p) (2010, methodology): “The author of [7] derives conclusions using assumptions on the internal structure of the network from numerical simulations on randomly generated networks of 1000 nodes.”
Regular rates of popular culture change reflect random copying (2007, methodology): “Applied here on the societal scale, the random-copying model simply assumes a constant proportion of innovators in the population, as often assumed in epidemiological models applied to binary-choice culture change (e.g., Dodds & Watts, 2005; Watts, 2002).”
Emotions and Information Diffusion in Social Media—Sentiment of Microblogs and Sharing Behavior (2013, background): “, connectivity or centrality), which allows them to influence a disproportionately large number of others—also indirectly via a cascade of influence [75].”
The Network Structure of Exploration and Exploitation (2007, background): “Newman, M. E. J., and D. Watts 1999 “Renormalization group analy- sis of the small-world network model.””
The “New” Science of Networks (2004, background): “…seed (even a single infective may sufﬁce), whereas models that embody nontrivial thresholds require an initial critical mass—that is, a ﬁnite fraction of the population—before can only occur for social contagion when the connectivity of the network is neither too sparse nor too dense (Watts 2002).”
The Economic Consequences of Social Network Structure (2017, neutral): “It is thus possible that two societies with slightly different densities could experience 17For surveys see Jackson and Yariv (2011); Lamberson (2016). very different responses to the same diffusion process (e.g., Watts (2002); Lopez-Pintado (2008)).”
Patterns of Influence in a Recommendation Network (2006, methodology): “Theoretical analysis of cascades on random graphs is provided in [16], using a threshold model.”
Networks formed from interdependent networks (2011, methodology): “For n= 1, we obtain the known result pc=1/k, equation (11), of an Erdős–Rényi network and P∞(pc) = 0, which corresponds to a continuous second-order phase transition.”