scholarly journals Boundedly Rational Opinion Dynamics in Directed Social Networks: Theory and Experimental Evidence

2014 ◽  
Author(s):  
Pietro Battiston ◽  
Luca Stanca
Keyword(s):  
Social Networks ◽  
Experimental Evidence ◽  
Opinion Dynamics

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.

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 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

scholarly journals The robustness of reciprocity: Experimental evidence that each form of reciprocity is robust to the presence of other forms of reciprocity

2020 ◽  
Vol 6 (23) ◽  
pp. eaba0504
Author(s):  
David Melamed ◽  
Brent Simpson ◽  
Jered Abernathy
Keyword(s):  
Social Networks ◽  
Prosocial Behavior ◽  
Experimental Evidence ◽  
Real World ◽  
Strong Support ◽  
Theoretical Models ◽  
Current Understanding ◽  
The Real ◽  
Topological Features

Prosocial behavior is paradoxical because it often entails a cost to one’s own welfare to benefit others. Theoretical models suggest that prosociality is driven by several forms of reciprocity. Although we know a great deal about how each of these forms operates in isolation, they are rarely isolated in the real world. Rather, the topological features of human social networks are such that people are often confronted with multiple types of reciprocity simultaneously. Does our current understanding of human prosociality break down if we account for the fact that the various forms of reciprocity tend to co-occur in nature? Results of a large experiment show that each basis of human reciprocity is remarkably robust to the presence of other bases. This lends strong support to existing models of prosociality and puts theory and research on firmer ground in explaining the high levels of prosociality observed in human social networks.

scholarly journals A two phase investment game for competitive opinion dynamics in social networks

2020 ◽  
Vol 57 (2) ◽  
pp. 102064 ◽  
Author(s):  
Swapnil Dhamal ◽  
Walid Ben-Ameur ◽  
Tijani Chahed ◽  
Eitan Altman
Keyword(s):  
Social Networks ◽  
Opinion Dynamics ◽  
Two Phase ◽  
Investment Game
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