An Opinion Interactive Model Based on Individual Persuasiveness
In order to study the formation process of group opinion in real life, we put forward a new opinion interactive model based on Deffuant model and its improved models in this paper because current models of opinion dynamics lack considering individual persuasiveness. Our model has following advantage...
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Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2015/345160 |
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doaj-9303429cadf442ed9563d32537b4f6512020-11-24T20:45:49ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52651687-52732015-01-01201510.1155/2015/345160345160An Opinion Interactive Model Based on Individual PersuasivenessXin Zhou0Bin Chen1Liang Liu2Liang Ma3Xiaogang Qiu4School of Information System and Management, National University of Defense Technology, Changsha 410073, ChinaSchool of Information System and Management, National University of Defense Technology, Changsha 410073, ChinaSchool of Information System and Management, National University of Defense Technology, Changsha 410073, ChinaSchool of Information System and Management, National University of Defense Technology, Changsha 410073, ChinaSchool of Information System and Management, National University of Defense Technology, Changsha 410073, ChinaIn order to study the formation process of group opinion in real life, we put forward a new opinion interactive model based on Deffuant model and its improved models in this paper because current models of opinion dynamics lack considering individual persuasiveness. Our model has following advantages: firstly persuasiveness is added to individual’s attributes reflecting the importance of persuasiveness, which means that all the individuals are different from others; secondly probability is introduced in the course of interaction which simulates the uncertainty of interaction. In Monte Carlo simulation experiments, sensitivity analysis including the influence of randomness, initial persuasiveness distribution, and number of individuals is studied at first; what comes next is that the range of common opinion based on the initial persuasiveness distribution can be predicted. Simulation experiment results show that when the initial values of agents are fixed, no matter how many times independently replicated experiments, the common opinion will converge at a certain point; however the number of iterations will not always be the same; the range of common opinion can be predicted when initial distribution of opinion and persuasiveness are given. As a result, this model can reflect and interpret some phenomena of opinion interaction in realistic society.http://dx.doi.org/10.1155/2015/345160 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xin Zhou Bin Chen Liang Liu Liang Ma Xiaogang Qiu |
spellingShingle |
Xin Zhou Bin Chen Liang Liu Liang Ma Xiaogang Qiu An Opinion Interactive Model Based on Individual Persuasiveness Computational Intelligence and Neuroscience |
author_facet |
Xin Zhou Bin Chen Liang Liu Liang Ma Xiaogang Qiu |
author_sort |
Xin Zhou |
title |
An Opinion Interactive Model Based on Individual Persuasiveness |
title_short |
An Opinion Interactive Model Based on Individual Persuasiveness |
title_full |
An Opinion Interactive Model Based on Individual Persuasiveness |
title_fullStr |
An Opinion Interactive Model Based on Individual Persuasiveness |
title_full_unstemmed |
An Opinion Interactive Model Based on Individual Persuasiveness |
title_sort |
opinion interactive model based on individual persuasiveness |
publisher |
Hindawi Limited |
series |
Computational Intelligence and Neuroscience |
issn |
1687-5265 1687-5273 |
publishDate |
2015-01-01 |
description |
In order to study the formation process of group opinion in real life, we put forward a new opinion interactive model based on Deffuant model and its improved models in this paper because current models of opinion dynamics lack considering individual persuasiveness. Our model has following advantages: firstly persuasiveness is added to individual’s attributes reflecting the importance of persuasiveness, which means that all the individuals are different from others; secondly probability is introduced in the course of interaction which simulates the uncertainty of interaction. In Monte Carlo simulation experiments, sensitivity analysis including the influence of randomness, initial persuasiveness distribution, and number of individuals is studied at first; what comes next is that the range of common opinion based on the initial persuasiveness distribution can be predicted. Simulation experiment results show that when the initial values of agents are fixed, no matter how many times independently replicated experiments, the common opinion will converge at a certain point; however the number of iterations will not always be the same; the range of common opinion can be predicted when initial distribution of opinion and persuasiveness are given. As a result, this model can reflect and interpret some phenomena of opinion interaction in realistic society. |
url |
http://dx.doi.org/10.1155/2015/345160 |
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