TY - JOUR
T1 - Finite-size effects on the convergence time in continuous-opinion dynamics
AU - Jo, Hang Hyun
AU - Masuda, Naoki
N1 - Funding Information:
H.-H.J. thanks J. D. Noh for fruitful comments on the initial draft and acknowledges financial support by Basic Science Research Program through the National Research Foundation of Korea (NRF) grant funded by the Ministry of Education (NRF-2018R1D1A1A09081919) and by the Catholic University of Korea, Research Fund, 2020. N.M. acknowledges support from AFOSR European Office (under Grant No. FA9550-19-1-7024), the Nakatani Foundation, and the Sumitomo Foundation.
Publisher Copyright:
© 2021 American Physical Society.
PY - 2021/7
Y1 - 2021/7
N2 - We study finite-size effects on the convergence time in a continuous-opinion dynamics model. In the model, each individual's opinion is represented by a real number on a finite interval, e.g., [0,1], and a uniformly randomly chosen individual updates its opinion by partially mimicking the opinion of a uniformly randomly chosen neighbor. We numerically find that the characteristic time to the convergence increases as the system size increases according to a particular functional form in the case of lattice networks. In contrast, unless the individuals perfectly copy the opinion of their neighbors in each opinion updating, the convergence time is approximately independent of the system size in the case of regular random graphs, uncorrelated scale-free networks, and complete graphs. We also provide a mean-field analysis of the model to understand the case of the complete graph.
AB - We study finite-size effects on the convergence time in a continuous-opinion dynamics model. In the model, each individual's opinion is represented by a real number on a finite interval, e.g., [0,1], and a uniformly randomly chosen individual updates its opinion by partially mimicking the opinion of a uniformly randomly chosen neighbor. We numerically find that the characteristic time to the convergence increases as the system size increases according to a particular functional form in the case of lattice networks. In contrast, unless the individuals perfectly copy the opinion of their neighbors in each opinion updating, the convergence time is approximately independent of the system size in the case of regular random graphs, uncorrelated scale-free networks, and complete graphs. We also provide a mean-field analysis of the model to understand the case of the complete graph.
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U2 - 10.1103/PhysRevE.104.014309
DO - 10.1103/PhysRevE.104.014309
M3 - Article
C2 - 34412253
AN - SCOPUS:85111274208
SN - 2470-0045
VL - 104
JO - Physical Review E
JF - Physical Review E
IS - 1
M1 - 014309
ER -