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Thresholds in the resilience of modular social networks to invasion by defectors

Wechsler, Daniel; Bascompte, Jordi (2019). Thresholds in the resilience of modular social networks to invasion by defectors. Journal of Theoretical Biology, 460:56-63.

Abstract

Cooperative interactions constitute the backbone of many biological and social systems. Since cooperation is prone to exploitation, these systems must incorporate mechanisms that prevent the spreading of defective behaviors. One such mechanism is modularity, i.e., the tendency of a social network to be organized in modules, where individuals within a module tend to interact strongly among themselves while avoiding interacting with individuals from other modules. This structure allows cooperation to prevail by having modules of cooperative individuals with a limited exposure to defectors. To address the rate and shape of the effect of modularity on the resilience of cooperation, here we study a variant of the Prisoner’s Dilemma on modular networks. Our simulations reveal a sharp transition between a resilient and a vulnerable regime as modularity exceeds a critical threshold. By using a simplified mathematical model, we show that the observed threshold is equivalent to the epidemic threshold found in a certain class of SIR models. This allows us to derive an explicit condition under which a cooperative society is expected to be resilient to invasive defectors.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Modeling and Simulation
Life Sciences > General Biochemistry, Genetics and Molecular Biology
Life Sciences > General Immunology and Microbiology
Life Sciences > General Agricultural and Biological Sciences
Physical Sciences > Applied Mathematics
Uncontrolled Keywords:General Biochemistry, Genetics and Molecular Biology, Modelling and Simulation, Statistics and Probability, General Immunology and Microbiology, Applied Mathematics, General Agricultural and Biological Sciences, General Medicine
Language:English
Date:1 January 2019
Deposited On:15 Mar 2019 08:30
Last Modified:30 Aug 2024 03:36
Publisher:Elsevier
ISSN:0022-5193
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.jtbi.2018.10.018
PubMed ID:30296450
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