Interacting Social Processes on Interconnected Networks.

Interacting Social Processes on Interconnected Networks.
复制标题

DOI:
10.1371/journal.pone.0163593
复制
发表时间:
2016
期刊:
影响因子:
3.7
通讯作者:
Braunstein LA
Braunstein LA
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Alvarez-Zuzek LG;La Rocca CE;Vazquez F;Braunstein LA

文献摘要

参考文献

被引文献

相似文献

我们提出并研究了两个不同的动态过程之间的相互作用的模型-一个意见的形成和其他决策-在两个互联网络A和B。网络A上的意见动态对应于M模型,其中每个代理的状态可以取四个可能值之一(S =-2,-1,1,2),描述其对给定问题的同意程度。成为极端主义者(S = ±2)或温和主义者(S = ±1)的可能性由强化参数r ≥ 0控制。网络B上的决策动态类似于艾布拉姆斯-斯特罗加茨模型,其中代理人可以赞成(S = +1)或反对(S =-1)这个问题。一个智能体改变其状态的概率与保持相反状态的邻居的分数的β次方成正比。从一个两极分化的情况下,网络A的所有代理持有积极的方向,而网络B的所有代理有一个消极的方向,我们探讨的条件下,其中一个动力压倒其他,强加其初始方向。我们发现,对于给定的β值,当强化克服交叉值r*(β)时,两个网络系统在正状态(网络A的初始状态)中达成共识,而当r < r*(β)时,两个网络系统在负状态中达成共识。在r − β相空间中,系统在临界阈值βc处表现出一个转变,从β < βc时两个取向共存到β > βc时一个取向占主导地位。我们开发了一个分析平均场的方法,给出了一个洞察这些制度,并表明,这两个动态是等价的沿着交叉线(r*,β*)。
We propose and study a model for the interplay between two different dynamical processes –one for opinion formation and the other for decision making– on two interconnected networks A and B. The opinion dynamics on network A corresponds to that of the M-model, where the state of each agent can take one of four possible values (S = −2,−1, 1, 2), describing its level of agreement on a given issue. The likelihood to become an extremist (S = ±2) or a moderate (S = ±1) is controlled by a reinforcement parameter r ≥ 0. The decision making dynamics on network B is akin to that of the Abrams-Strogatz model, where agents can be either in favor (S = +1) or against (S = −1) the issue. The probability that an agent changes its state is proportional to the fraction of neighbors that hold the opposite state raised to a power β. Starting from a polarized case scenario in which all agents of network A hold positive orientations while all agents of network B have a negative orientation, we explore the conditions under which one of the dynamics prevails over the other, imposing its initial orientation. We find that, for a given value of β, the two-network system reaches a consensus in the positive state (initial state of network A) when the reinforcement overcomes a crossover value r*(β), while a negative consensus happens for r < r*(β). In the r − β phase space, the system displays a transition at a critical threshold βc, from a coexistence of both orientations for β < βc to a dominance of one orientation for β > βc. We develop an analytical mean-field approach that gives an insight into these regimes and shows that both dynamics are equivalent along the crossover line (r*, β*).
DOI: 10.1007/s100510050410
发表时间: 1998-08-01
影响因子: 1.6
作者:
Galam, S;Chopard, B;Droz, M
通讯作者: Droz, M
DOI: 10.1103/physrevlett.111.128701
发表时间: 2013-09-17
影响因子: 8.6
作者:
Granell, Clara;Gomez, Sergio;Arenas, Alex
通讯作者: Arenas, Alex
DOI: 10.1103/physrevx.6.021002
发表时间: 2016-04-01
期刊: PHYSICAL REVIEW X
影响因子: 12.5
作者:
Hackett, A.;Cellai, D.;Gleeson, J. P.
通讯作者: Gleeson, J. P.
DOI: 10.1088/1742-5468/2009/10/p10024
发表时间: 2009-10-01
影响因子: 2.4
作者:
Angeles Serrano, M.;Klemm, Konstantin;San Miguel, Maxi
通讯作者: San Miguel, Maxi
由相互依存的网络组成的网络
DOI: 10.1038/nphys2180
发表时间: 2012-01-01
期刊: NATURE PHYSICS
影响因子: 19.6
作者:
Gao, Jianxi;Buldyrev, Sergey V.;Havlin, Shlomo
通讯作者: Havlin, Shlomo