A two-step communication opinion dynamics model with self-persistence and influence index for social networks based on the DeGroot model

2020 ◽  
Vol 519 ◽  
pp. 363-381 ◽  
Author(s):  
Qinyue Zhou ◽  
Zhibin Wu ◽  
Abdulrahman H. Altalhi ◽  
Francisco Herrera
Keyword(s):  
Social Networks ◽  
Opinion Dynamics ◽  
Dynamics Model ◽  
Degroot Model

OPINION DIFFUSION ON MULTILAYER SOCIAL NETWORKS

2017 ◽  
Vol 20 (06n07) ◽  
pp. 1750015 ◽  
Author(s):  
HAI-BO HU ◽  
CANG-HAI LI ◽  
QING-YING MIAO
Keyword(s):  
Social Networks ◽  
Opinion Dynamics ◽  
Coupling Agents ◽  
Dynamics Model ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Influence Matrix ◽  
Strongly Connected ◽  
Degroot Model ◽  
Multilayer Social Networks

In this paper, to reveal the influence of multilayer network structure on opinion diffusion in social networks, we study an opinion dynamics model based on DeGroot model on multilayer networks. We find that if the influence matrix integrating the information of connectedness for each layer and correlation between layers is strongly connected and aperiodic, all agents’ opinions will reach a consensus. However, if there are stubborn agents in the networks, regular agents’ opinions will finally be confined to the convex combinations of the stubborn agents’. Specifically, if all stubborn agents hold the same opinion, even if the agents only exist on a certain layer, their opinions will diffuse to the entire multilayer networks. This paper not only characterizes the influence of multilayer network topology and agent attribute on opinion diffusion in a holistic way, but also demonstrates the importance of coupling agents which play an indispensable role in some social and economic situations.

Multi-state voter model on weighted social networks with committed agents

2014 ◽  
Vol 25 (07) ◽  
pp. 1450022 ◽  
Author(s):  
Saijun Chen ◽  
Haibo Hu ◽  
Jun Chen ◽  
Zhigao Chen
Keyword(s):  
Social Networks ◽  
Numerical Simulations ◽  
Opinion Dynamics ◽  
The Other ◽  
Voter Model ◽  
Scaling Exponent ◽  
Dynamics Model ◽  
Topological Structures ◽  
A Value ◽  
Dynamics Models

There exist scaling correlations between the edge weights and the nodes' degrees in weighted social networks. Based on the empirical findings, we study a multi-state voter model on weighted social networks where the weight is given by the product of agents' degrees raised to a power θ and there exist persistent individuals whose opinions are independent of those of their friends. We find that the fraction of each opinion will converge to a value which only relates to the degrees of initial committed agents and the scaling exponent θ. The analytical predictions are verified by numerical simulations. The model indicates that agents' degrees and scaling exponent can significantly influence the final coexistence or consensus state of opinions. We also study the influence of degree mixing characteristics on the dynamics model by numerical simulations and discuss the relation between the model and the other related opinion dynamics models on social networks with different topological structures and initial configurations.

scholarly journals Opinion Dynamics and the Inevitability of a Polarised and Homophilic Society

2021 ◽  
Author(s):  
Rafael Prieto Curiel
Keyword(s):  
Social Networks ◽  
Human Factors ◽  
Small Perturbation ◽  
Opinion Dynamics ◽  
Selective Exposure ◽  
Complex Model ◽  
Dynamics Model ◽  
Starting Point ◽  
The Social ◽  
Extreme Sensitivity

A polarised society is frequently observed among ideological extremes, despite individual and collective efforts to reach a consensual opinion. Human factors, such as the tendency to interact with similar people and the reinforcement of such homophilic interactions or the selective exposure and assimilation to distinct views are some of the mechanisms why opinions might evolve into a more divergent distribution. A complex model in which individuals are exposed to alternating waves of propaganda which fully support different extreme views is considered here within an opinion dynamics model. People exposed to different extreme narratives adopt and share them with their peers based on the persuasiveness of the propaganda and are mixed with their previous opinions based on the volatility of opinions to form a new individual view. Social networks help capture elements such as homophily, whilst persuasiveness and memory capture bias assimilation and the exposure to ideas inside and outside echo chambers. The social levels of homophily and polarisation after iterations of people being exposed to extreme narratives define distinct trajectories of society becoming more or less homophilic and reaching extremism or consensus. There is extreme sensitivity to the parameters so that a small perturbation to the persuasiveness or the memory of a network in which consensus is reached could lead to the polarisation of opinions, but there is also unpredictability of the system since even under the same starting point, a society could follow substantially different trajectories and end with a consensual opinion or with extreme polarising views.

PHYSICS OF THE MIND: OPINION DYNAMICS AND DECISION MAKING PROCESSES BASED ON A BINARY NETWORK MODEL

2008 ◽  
Vol 22 (25n26) ◽  
pp. 4482-4494 ◽  
Author(s):  
F. V. KUSMARTSEV ◽  
KARL E. KÜRTEN
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Chaotic Behavior ◽  
Opinion Dynamics ◽  
Human Mind ◽  
Critical Parameters ◽  
Opinion Formation ◽  
Natural Catastrophes ◽  
Risk Condition ◽  
Binary Network

We propose a new theory of the human mind. The formation of human mind is considered as a collective process of the mutual interaction of people via exchange of opinions and formation of collective decisions. We investigate the associated dynamical processes of the decision making when people are put in different conditions including risk situations in natural catastrophes when the decision must be made very fast or at national elections. We also investigate conditions at which the fast formation of opinion is arising as a result of open discussions or public vote. Under a risk condition the system is very close to chaos and therefore the opinion formation is related to the order disorder transition. We study dramatic changes which may happen with societies which in physical terms may be considered as phase transitions from ordered to chaotic behavior. Our results are applicable to changes which are arising in various social networks as well as in opinion formation arising as a result of open discussions. One focus of this study is the determination of critical parameters, which influence a formation of stable mind, public opinion and where the society is placed “at the edge of chaos”. We show that social networks have both, the necessary stability and the potential for evolutionary improvements or self-destruction. We also show that the time needed for a discussion to take a proper decision depends crucially on the nature of the interactions between the entities as well as on the topology of the social networks.

scholarly journals Opinion Dynamics in Social Networks through Mean-Field Games

2016 ◽  
Vol 54 (6) ◽  
pp. 3225-3257 ◽  
Author(s):  
D. Bauso ◽  
H. Tembine ◽  
T. Başar
Keyword(s):  
Social Networks ◽  
Mean Field ◽  
Opinion Dynamics ◽  
Mean Field Games
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