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

2017 ◽  
Vol 28 (05) ◽  
pp. 1750058 ◽  
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.

Autonomy-oriented proximity mobile social network modeling in smart city for emergency rescue

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110612
Author(s):  
Zhao Chunxiao ◽  
Guo Junjie
Keyword(s):  
Social Network ◽  
Network Model ◽  
Smart City ◽  
Disaster Relief ◽  
Network Modeling ◽  
Mobile Social Network ◽  
Emergency Rescue ◽  
Routing Strategy ◽  
Social Network Modeling ◽  
Post Disaster

Nearest neighbor mobile social network means that movers approaching in position communicate through their social sensors, which is called Proximity Mobile Social Network. Proximity Mobile Social Network can provide more social and business opportunities for users. To carry out disaster relief work in post-disaster environment, we need to collect incident information during the search process and report to the sink in time. Proximity Mobile Social Network provides flexible systems for emergency handling and disaster relief. Therefore, how to find a better data forwarding and routing strategy is the key problem of post-disaster rescue, and the research of user mobility model is the basis of the above problems. This article presents an Autonomy-Oriented Proximity Mobile Social Network modeling for emergency rescue in smart city, which simulates the network operating environment. First, we verify the performance of Autonomy-Oriented Proximity Mobile Social Network model in terms of self-organization, scale-free, aggregation, and community structure. Then, the rescue efficiency is discussed through the coverage of mobile sensors. Finally, performance of the routing strategy based on Autonomy-Oriented Proximity Mobile Social Network model is analyzed, and the effectiveness of the method is proved.

Social Space in Simulation Models

2014 ◽  
pp. 200-219
Author(s):  
Davide Nunes ◽  
Luis Antunes
Keyword(s):  
Social Relations ◽  
Social Space ◽  
Opinion Dynamics ◽  
Simulation Models ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Space Design ◽  
Network Topologies ◽  
Multiple Interaction ◽  
Set Up

In real world scenarios, the formation of consensus is a self-organisation process by which actors have to make a joint assessment about a target subject, be it a decision making problem or the formation of a collective opinion. In social simulation, models of opinion dynamics tackle the opinion formation phenomena. These models try to make an assessment, for instance, of the ideal conditions that lead an interacting group of agents to opinion consensus, polarisation or fragmentation. This chapter investigates the role of social relation structure in opinion dynamics and consensus formation. The authors present an agent-based model that defines social relations as multiple concomitant social networks and explore multiple interaction games in this structural set-up. They discuss the influence of complex social network topologies where actors interact in multiple distinct networks. The chapter builds on previous work about social space design with multiple social relations to determine the influence of such complex social structures in a process such as opinion formation.

scholarly journals Group Measures and Modeling for Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Vincent Levorato
Keyword(s):  
Complex System ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Modeling ◽  
Complex Interactions ◽  
Social Network Modeling

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.

Doubly threshold graphs for social network modeling

2016 ◽  
Author(s):  
Vida Ravanmehr ◽  
Sadegh Bolouki ◽  
Gregory J. Puleo ◽  
Olgica Milenkovic
Keyword(s):  
Social Network ◽  
Network Modeling ◽  
Threshold Graphs ◽  
Social Network Modeling

scholarly journals Development of online tool using Social Network Modeling concepts and Quality Control tools for faster product development

2020 ◽  
Author(s):  
Yoshida Rao
Keyword(s):  
Quality Control ◽  
Social Network ◽  
Knowledge Base ◽  
Network Modeling ◽  
Field Analysis ◽  
New Paradigm ◽  
The Public ◽  
The People ◽  
Social Network Modeling ◽  
Technical Terms

Earlier engineering was done by few people. But now with ever increasing knowledge base with the public, there is need to tap that source. But this tapping of knowledge base of the public cannot be done in technical terms. There is need to express knowledge in non technical terms by use of logical reasoning, modeling of ideas, etc. Seeing these non technical details on website, some people can even put their responses, or ask for clarification of some points. Now if designers see this information they can answer those queries. Modern engineering is not limited to the handful designers alone, country has a large knowledge base in public, but a company cannot hire all people, so there needs to place a mechanism by which designers can come in contact with the people, understand and incorporate their feedback and answer their queries.Quality control tools (like flowchart, Cause-effect or fishbone diagrams, force field analysis, interrelations digraph, affinity diagram, and variability matrix) have been quite popular as they explain the engineering processes in a non technical way, yet they analyze the underlying process thoroughly.With the advent of modern computers, a new paradigm has been opened in terms of Social Network analysis, which connects people in a faster manner and lead to quicker information flow. In this project we propose to use the above mentioned Quality Control tools with Social Network modeling concepts to bring every bit of information available with the people at lower working level in a systematic and structured manner in the front of senior decision making level.

The role of fanatics in consensus formation

2015 ◽  
Vol 26 (03) ◽  
pp. 1550029 ◽  
Author(s):  
Semra Gündüç
Keyword(s):  
Finite Size ◽  
Opinion Dynamics ◽  
Scaling Relations ◽  
Scaling Relation ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Social Actors ◽  
Size Dependent ◽  
Proposed Model ◽  
Formation Behavior

A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.

scholarly journals The Impact of Community Structure on the Convergence Time of Opinion Dynamics

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
An Lu ◽  
Chunhua Sun ◽  
Yezheng Liu
Keyword(s):  
Community Structure ◽  
Social Network ◽  
Social Influence ◽  
Opinion Dynamics ◽  
Matrix Analysis ◽  
Convergence Time ◽  
Influence Matrix ◽  
The Social ◽  
The Impact ◽  
Second Largest Eigenvalue

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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