Opinion Dynamics Control in a Social Network with a Communication Structure

We analyze the convergence time of opinion dynamics in a social network with community structure. Using matrix analysis, we prove that the convergence time is determined by the second largest eigenvalue modulus. This modulus is close to 1 if the social influence matrix is nearly uncoupled. Furthermore, we discuss and analyze the factors of community structure affecting the convergence time.

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Social Network Analysis (SNA) for Construction Projects' Team Communication Structure Optimization

Construction Research Congress 2014 ◽

10.1061/9780784413517.207 ◽

2014 ◽

Cited By ~ 9

Author(s):

Andreas Malisiovas ◽

Xinyi Song

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Construction Projects ◽

Structure Optimization ◽

Team Communication ◽

Communication Structure

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Consensus formation simulation in a social network modeling controversial opinion dynamics with pairwise interactions

International Journal of Modern Physics C ◽

10.1142/s0129183117500589 ◽

2017 ◽

Vol 28 (05) ◽

pp. 1750058 ◽

Cited By ~ 3

Author(s):

María G. Medina-Guevara ◽

Jorge E. Macías-Díaz ◽

Armando Gallegos ◽

Héctor Vargas-Rodríguez

Keyword(s):

Social Network ◽

Network Modeling ◽

Opinion Dynamics ◽

Opinion Formation ◽

Consensus Formation ◽

Pairwise Interactions ◽

Finite Difference Equations ◽

The Social ◽

Social Network Modeling ◽

Strong Consensus

In this work, we consider a system of coupled finite-difference equations which incorporates a variety of opinion formation models, and use it to describe the dynamics of opinions on controversial subjects. The social network consists of a finite number of agents with pairwise interactions at discrete times. Meanwhile, the opinion of each agent is updated following a general nonlinear law which considers parameters identified as the personal constants of each of the members. We establish conditions that guarantee the existence of global attracting points (strong consensus) and intervals (weak consensus). Moreover, we note that these conditions are independent of the weight matrix and the number of agents of the network. Two particular scenarios are investigated numerically in order to confirm the validity of the analytical results.

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Trust and manipulation in social networks

Network Science ◽

10.1017/nws.2015.34 ◽

2016 ◽

Vol 4 (2) ◽

pp. 216-243 ◽

Cited By ~ 4

Author(s):

MANUEL FÖRSTER ◽

ANA MAULEON ◽

VINCENT J. VANNETELBOSCH

Keyword(s):

Social Networks ◽

Social Network ◽

Opinion Dynamics ◽

Information Aggregation ◽

Common Interest ◽

Opinion Leadership ◽

Weighted Averages

AbstractWe investigate the role of manipulation in boundedly rational opinion dynamics. Agents are subject to persuasion bias and repeatedly communicate with their neighbors in a social network. They can exert effort to manipulate trust in the opinions of others in their favor and update their opinions about some issue of common interest by taking weighted averages of neighbors' opinions. We show that manipulation can connect a segregated society and thus lead to mutual consensus. Second, we show that manipulation fosters opinion leadership; and surprisingly agents with low trust in their own opinion might get more influential even by being manipulated. Finally, comparative simulations reveal that manipulation is beneficial to information aggregation when preferences and abilities for manipulation are homogeneous, but detrimental in case abilities are concentrated at few powerful agents.

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