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  On Bipartite Consensus of Bounded Confidence Models for Opinion Dynamics

He, G., Liu, J., Wu, Y., Fang, J.-A. (2020): On Bipartite Consensus of Bounded Confidence Models for Opinion Dynamics. - International Journal of Control, Automation and Systems, 18, 2, 303-312.
https://doi.org/10.1007/s12555-019-0138-x

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 Creators:
He, Guang1, Author              
Liu, Jing2, Author
Wu, Yanlei2, Author
Fang, Jian-An2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: In this paper, the bipartite consensus problem is investigated for bounded confidence (BC) models. Different from the existing results concerning clustering characteristic of BC models, we investigate under which circumstances BC models can achieve bipartite consensus. About the classic BC model, we obtain a sufficient and necessary condition for bipartite consensus problem. For the signed BC model, several bipartite consensus criteria are obtained. The obtained criteria reveal that the dynamic of the signed BC model more dependents on the initial opinions. Finally, several examples are provided to illustrate the effectiveness of the obtained results.

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 Dates: 2019-09-232020-02
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s12555-019-0138-x
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
MDB-ID: No data to archive
Working Group: Network- and machine-learning-based prediction of extreme events
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Title: International Journal of Control, Automation and Systems
Source Genre: Journal, SCI, Scopus
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Pages: - Volume / Issue: 18 (2) Sequence Number: - Start / End Page: 303 - 312 Identifier: Publisher: Springer
Other: 2005-4092
ISSN: 1598-6446
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/international-journal-control-automation-systems
Publisher: Springer