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 -