Three-State Opinion Formation Model on Adaptive Networks and Time to Consensus

2014 ◽  
pp. 73-84
Author(s):  
Degang Wu ◽  
Kwok Yip Szeto
Keyword(s):  
Adaptive Networks ◽  
Formation Model ◽  
Opinion Formation

scholarly journals A three-state opinion formation model for financial markets

2021 ◽  
pp. 126527
Author(s):  
Bernardo J. Zubillaga ◽  
André L.M. Vilela ◽  
Chao Wang ◽  
Kenric P. Nelson ◽  
H. Eugene Stanley
Keyword(s):  
Financial Markets ◽  
Formation Model ◽  
Opinion Formation

Distributed prediction of solar farm status by probabilistic fuzzy opinion formation model

2018 ◽  
Vol 10 (4) ◽  
pp. 043508 ◽  
Author(s):  
Masoud Bashari ◽  
Mohammad-Reza Akbarzadeh-Totonchi
Keyword(s):  
Formation Model ◽  
Opinion Formation

Opinion formation on evolving and adaptive networks

2019 ◽  
Vol 2019 (1) ◽  
pp. 013202
Author(s):  
Jinyu Huang ◽  
Xiaogang Jin
Keyword(s):  
Adaptive Networks ◽  
Opinion Formation

Spontaneous emergence of a third position in an opinion formation model

2019 ◽  
Vol 521 ◽  
pp. 501-511
Author(s):  
Marcos E. Gaudiano ◽  
Jorge A. Revelli
Keyword(s):  
Formation Model ◽  
Opinion Formation

DYNAMICS WITH CO-EVOLUTION OF INDIVIDUAL INCLINATION AND OPINION

2011 ◽  
Vol 22 (01) ◽  
pp. 51-62 ◽  
Author(s):  
FEI XIONG ◽  
YUN LIU ◽  
ZHENJIANG ZHANG
Keyword(s):  
Opinion Dynamics ◽  
Spin Systems ◽  
Voter Model ◽  
Formation Model ◽  
Opinion Formation ◽  
Final State ◽  
Memory Length ◽  
Slowing Down ◽  
The Past ◽  
The Individual

Based on the voter model, we present a new opinion formation model which takes into account the evolution of both opinions and individual inclinations. A memory-based inclination is developed gradually during the process of social interaction; however, if the individual inclination gets strong enough, it will react to opinion dynamics. We assume that an individual inclination increases with the number of times the individual has held its most frequent opinion in the past interactions. As a result of inclination choices the transition rate following neighbors decreases, thus slowing down the microscopic dynamics. Analytical and simulation results indicate the system under the action of opinion inclinations evolves to a more polarized state for average opinion. The appearance of extremists holding the minority opinion is observed in the final state, where one opinion predominates. It is also found that the stable opinion and relaxation time depend on network topology and memory length. Moreover, this model is not only valid to the voter model, but can also be applied to other spin systems.

Prediction of collective opinion in consensus formation

2014 ◽  
Vol 25 (04) ◽  
pp. 1450002 ◽  
Author(s):  
Lei Hou ◽  
Jianguo Liu ◽  
Xue Pan ◽  
Wen-Jun Song ◽  
Xu-Dong Li
Keyword(s):  
Steady State ◽  
Theoretical Analysis ◽  
Linear Relationship ◽  
Correlation Coefficient ◽  
Opinion Leaders ◽  
Formation Model ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Final State ◽  
Formation Dynamics

In the consensus formation dynamics, the effect of leaders and interventions have been widely studied for it has many applications such as in politics and commerce. However, the problem is how to know if it is necessary for one to make an intervention. In this paper, we theoretically propose a method for predicting the tendency and final state of collective opinion. By giving each agent a conviction ci which measures the ability to insist on his opinion, we present an opinion formation model in which agents with high convictions naturally show up properties of the opinion leaders. Results reveal that, although each agent initially gets an opinion evenly distributed in the range [-1, 1], the collective opinion of the steady-state may deviate to the positive or negative direction because of the initial bias of the leaders' opinions. We further get the correlation coefficient of the linear relationship between the collective opinion and the initial bias according to both the experimental and theoretical analysis. Thus, we could predict the final state at the very beginning of the dynamic only if we get the opinions of a small portion of the population. The prediction would afford us more time and opportunities to make reactions and interventions.

AN OPINION FORMATION MODEL WITH TWO STAGES

2007 ◽  
Vol 18 (08) ◽  
pp. 1231-1242 ◽  
Author(s):  
BO SHEN ◽  
YUN LIU
Keyword(s):  
Formation Process ◽  
Formation Model ◽  
Opinion Formation ◽  
Initial State ◽  
Social Phenomena ◽  
Proposed Model ◽  
Crucial Effect ◽  
The Social ◽  
Two Stages ◽  
First Time

The opinion formation process is a general phenomenon in community and society. In recent years, several models of opinion formation have been proposed; however, most models mainly focus on describing views exchange between individuals and interaction between individuals and the environment. In this paper, we present an opinion formation model which takes into account the initial state of opinions and the contacting process with topics. The model involves two stages. The first one is the process in which individuals contact a given topic for the first time and the second one is the social interaction process between individuals. Using the proposed model, we simulate opinion formation process with several sets of parameters. Simulation results indicate that the proposed model may be successfully used for opinion formation simulations. It is also found that the initial state and contacting process have significant influence on opinion formation. Moreover, the model could be helpful for understanding some social phenomena such as quick formation of public opinion about certain topic and the crucial effect of small fluctuations on opinion distribution.

Voter model on adaptive networks

2021 ◽  
Author(s):  
Jinming Du
Keyword(s):  
Network Topology ◽  
Statistical Physics ◽  
Evolutionary Game ◽  
Dynamic Networks ◽  
Real Data ◽  
Voter Model ◽  
Adaptive Networks ◽  
Opinion Formation ◽  
Basic Model ◽  
Individual Behaviors

Abstract Voter model is an important basic model in statistical physics. In recent years, it has been more and more used to describe the process of opinion formation in sociophysics. In real complex systems, the interactive network of individuals is dynamically adjusted, and the evolving network topology and individual behaviors affect each other. Therefore, we propose a linking dynamics to describe the coevolution of network topology and individual behaviors in this paper, and study the voter model on the adaptive network. We theoretically analyze the properties of the voter model, including consensus probability and time. The evolution of opinions on dynamic networks is further analyzed from the perspective of evolutionary game. Finally, a case study of real data is shown to verify the effectiveness of the theory.

PUBLIC OPINION FORMATION MODEL BASED ON OPINION ENTROPY

2013 ◽  
Vol 24 (11) ◽  
pp. 1350080 ◽  
Author(s):  
YUE WU ◽  
YONG HU ◽  
XIAO-HAI HE
Keyword(s):  
Public Opinion ◽  
Shannon Entropy ◽  
Quantitative Measurement ◽  
Formation Model ◽  
Opinion Formation ◽  
The Public ◽  
Model Based ◽  
Simulation Results ◽  
High Control ◽  
Short Time

In this paper, we introduce the concept of opinion entropy based on Shannon entropy, which is used to describe the uncertainty of opinions. With opinion entropy, we further present a public opinion formation model, and simulate the process of public opinion formation under various controlled conditions. Simulation results on the Holme–Kim network show that the opinion entropy will reduce to zero, and all individuals will hold the opinion of agreeing with the topic, only by adjusting the cons' opinions with a high control intensity. Controlling the individuals with big degree can bring down the opinion entropy in a short time. Besides, extremists do not easily change their opinion entropy. Compared with previous opinion clusters, opinion entropy provides a quantitative measurement for the uncertainty of opinions. Moreover, the model can be helpful for understanding the dynamics of opinion entropy, and controlling the public opinion.

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