Long ties accelerate noisy threshold-based contagions

Dean Eckles (), Elchanan Mossel, M. Amin Rahimian () and Subhabrata Sen
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Dean Eckles: Massachusetts Institute of Technology
Elchanan Mossel: Massachusetts Institute of Technology
M. Amin Rahimian: University of Pittsburgh
Subhabrata Sen: Harvard University

Nature Human Behaviour, 2024, vol. 8, issue 6, 1057-1064

Abstract: Abstract In widely used models of biological contagion, interventions that randomly rewire edges (generally making them ‘longer’) accelerate spread. However, recent work has argued that highly clustered, rather than random, networks facilitate the spread of threshold-based contagions, such as those motivated by myopic best response for adoption of new innovations, norms and products in games of strategic complement. Here we show that minor modifications to this model reverse this result, thereby harmonizing qualitative facts about how network structure affects contagion. We analyse the rate of spread over circular lattices with rewired edges and show that having a small probability of adoption below the threshold probability is enough to ensure that random rewiring accelerates the spread of a noisy threshold-based contagion. This conclusion is verified in simulations of empirical networks and remains valid with partial but frequent enough rewiring and when adoption decisions are reversible but infrequently so, as well as in high-dimensional lattice structures.

Date: 2024
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DOI: 10.1038/s41562-024-01865-0

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