Opinion evolution in adaptive complex networks
With the rapid development of information technology, information dissemination becomes more convenient, which makes public opinion events in the society happen frequently and become the focus. The report is written to study the process of opinion diversity and analyse the dynamic evolution relat...
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sg-ntu-dr.10356-1604192023-07-04T17:45:23Z Opinion evolution in adaptive complex networks Xu, Jiayuan Xiao Gaoxi School of Electrical and Electronic Engineering EGXXiao@ntu.edu.sg Engineering::Electrical and electronic engineering With the rapid development of information technology, information dissemination becomes more convenient, which makes public opinion events in the society happen frequently and become the focus. The report is written to study the process of opinion diversity and analyse the dynamic evolution relationship between the network structure and opinions to reveal the inherent law, which has very important practical significance. Based on the research of domestic and foreign scholars on complex networks theory and opinion dynamics, this paper uses computer simulation, theoretical modeling and analysis as methodology to reasonably abstract the interaction mode and behavior state between individuals in the network, and establishes a simulation model of opinion propagation on the complex network. The Deffaunt model is selected to conduct simulation according to the relationship between network topology structure and opinion communication. This report studies the influence of different tolerance threshold, opinion composition and rewiring probability on the evolution direction, speed and time respectively. The ”fundamental belief ” was introduced into the algorithm to make the simulated data more consistent with the reality. The experimental results show that the number of clusters when dynamic equilibrium is only related to the maximum tolerance. Finally, the report summarizes the above research and design, and evaluates the network structure change and evolution trend of network public opinion, and puts forward relevant suggestions for future research work. Master of Science (Communications Engineering) 2022-07-22T00:47:35Z 2022-07-22T00:47:35Z 2022 Thesis-Master by Coursework Xu, J. (2022). Opinion evolution in adaptive complex networks. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/160419 https://hdl.handle.net/10356/160419 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Xu, Jiayuan Opinion evolution in adaptive complex networks |
description |
With the rapid development of information technology, information dissemination
becomes more convenient, which makes public opinion events in the society
happen frequently and become the focus. The report is written to study
the process of opinion diversity and analyse the dynamic evolution relationship
between the network structure and opinions to reveal the inherent law, which
has very important practical significance. Based on the research of domestic
and foreign scholars on complex networks theory and opinion dynamics, this
paper uses computer simulation, theoretical modeling and analysis as methodology
to reasonably abstract the interaction mode and behavior state between
individuals in the network, and establishes a simulation model of opinion propagation
on the complex network. The Deffaunt model is selected to conduct
simulation according to the relationship between network topology structure and
opinion communication. This report studies the influence of different tolerance
threshold, opinion composition and rewiring probability on the evolution direction,
speed and time respectively. The ”fundamental belief ” was introduced into
the algorithm to make the simulated data more consistent with the reality. The
experimental results show that the number of clusters when dynamic equilibrium
is only related to the maximum tolerance. Finally, the report summarizes
the above research and design, and evaluates the network structure change and
evolution trend of network public opinion, and puts forward relevant suggestions
for future research work. |
author2 |
Xiao Gaoxi |
author_facet |
Xiao Gaoxi Xu, Jiayuan |
format |
Thesis-Master by Coursework |
author |
Xu, Jiayuan |
author_sort |
Xu, Jiayuan |
title |
Opinion evolution in adaptive complex networks |
title_short |
Opinion evolution in adaptive complex networks |
title_full |
Opinion evolution in adaptive complex networks |
title_fullStr |
Opinion evolution in adaptive complex networks |
title_full_unstemmed |
Opinion evolution in adaptive complex networks |
title_sort |
opinion evolution in adaptive complex networks |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/160419 |
_version_ |
1772827845347770368 |