We investigate different opinion formation models on adaptive network topologies. Depending on the dynamical process, rewiring can either (i) lead to the elimination of interactions between agents in different states, and accelerate the convergence to a consensus state or break the network in noninteracting groups or (ii), counterintuitively, favor the existence of diverse interacting groups for exponentially long times. The mean-field analysis allows us to elucidate the mechanisms at play. Strikingly, allowing the interacting agents to bear more than one opinion at the same time drastically changes the model's behavior and leads to fast consensus.
%0 Journal Article
%1 Nardini2008
%A Nardini, C.
%A Kozma, B.
%A Barrat, A.
%D 2008
%J Phys. Rev. Lett.
%K networks opinion-formation adaptive-networks voter-model graphs
%P 158701
%R 10.1103/PhysRevLett.100.158701
%T Who's talking first? Consensus or lack thereof in coevolving opinion formation models
%V 100
%X We investigate different opinion formation models on adaptive network topologies. Depending on the dynamical process, rewiring can either (i) lead to the elimination of interactions between agents in different states, and accelerate the convergence to a consensus state or break the network in noninteracting groups or (ii), counterintuitively, favor the existence of diverse interacting groups for exponentially long times. The mean-field analysis allows us to elucidate the mechanisms at play. Strikingly, allowing the interacting agents to bear more than one opinion at the same time drastically changes the model's behavior and leads to fast consensus.
@article{Nardini2008,
abstract = {We investigate different opinion formation models on adaptive network topologies. Depending on the dynamical process, rewiring can either (i) lead to the elimination of interactions between agents in different states, and accelerate the convergence to a consensus state or break the network in noninteracting groups or (ii), counterintuitively, favor the existence of diverse interacting groups for exponentially long times. The mean-field analysis allows us to elucidate the mechanisms at play. Strikingly, allowing the interacting agents to bear more than one opinion at the same time drastically changes the model's behavior and leads to fast consensus.},
added-at = {2011-01-13T13:26:13.000+0100},
author = {Nardini, C. and Kozma, B. and Barrat, A.},
biburl = {https://www.bibsonomy.org/bibtex/245e9812a02de20736ba3ee8fa4de3cf8/rincedd},
doi = {10.1103/PhysRevLett.100.158701},
file = {Nardini2008 - Who’s Talking First? Consensus or Lack Thereof in Coevolving Opinion Formation Models.pdf:Contact Processes/Nardini2008 - Who’s Talking First? Consensus or Lack Thereof in Coevolving Opinion Formation Models.pdf:PDF},
interhash = {35708c435f30378219a6842367711033},
intrahash = {45e9812a02de20736ba3ee8fa4de3cf8},
journal = {Phys. Rev. Lett.},
keywords = {networks opinion-formation adaptive-networks voter-model graphs},
pages = 158701,
timestamp = {2011-01-13T13:26:13.000+0100},
title = {Who's talking first? Consensus or lack thereof in coevolving opinion formation models},
volume = 100,
year = 2008
}