Loading...
Dynamical influence processes on networks: General theory and applications to social contagion
Harris, Kameron Decker Danforth, Christopher M. Dodds, Peter Sheridan
Harris, Kameron Decker
Danforth, Christopher M.
Dodds, Peter Sheridan
Citations
Altmetric:
License
http://rightsstatements.org/vocab/InC/1.0/
License
DOI
10.1103/PhysRevE.88.022816
Abstract
We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations. © 2013 American Physical Society.
Description
Date
2013-08-28
Journal Title
Journal ISSN
Volume Title
Publisher
Files
Loading...
Danforth2013a.pdf
Adobe PDF, 931.15 KB
Research Projects
Organizational Units
Journal Issue
Citation
Harris KD, Danforth CM, Dodds PS. Dynamical influence processes on networks: General theory and applications to social contagion. Physical Review E. 2013 Aug 28;88(2):022816.