Modelling diffusion of innovations in a social network
arXiv:cond-mat/0204141 · doi:10.1103/PhysRevE.66.026121
Abstract
A new simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information agents decide whether to upgrade their level or not balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.
4 pages, 5 figures. Final version accepted in PRE
References in corpus (5)
Cited by in corpus (19)
- Statistical physics of social dynamics
- Affinity Paths and Information Diffusion in Social Networks
- Absorbing Phase Transitions of Branching-Annihilating Random Walks
- Dynamic message-passing equations for models with unidirectional dynamics
- Nonequilibrium phase transition in a model for the propagation of innovations among economic agents
- Efficiency of Information Spreading in a population of diffusing agents
- Quantification of deviations from rationality with heavy-tails in human dynamics
- Analytical Investigation of Innovation Dynamics Considering Stochasticity in the Evaluation of Fitness
- A simple model for multiple-choice collective decision making
- Stochastic cellular automaton for the coagulation-fission-process 2A->3A, 2A->A
- Optimal community structure for social contagions
- Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model
- Equation-Free Multiscale Computations in Social Networks: from Agent-based Modelling to Coarse-grained Stability and Bifurcation Analysis
- Faster is More Different: Mean-Field Dynamics of Innovation Diffusion
- Dynamics of interacting information waves in networks
- Phase transitions in Paradigm models
- Optimization as a result of the interplay between dynamics and structure
- Tomography of random social networks
- Exact rank-reduction of network models