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    Opinion Dynamics With Cross-Coupling Topics: Modeling and Analysis

    78362.pdf (722.9Kb)
    Access Status
    Open access
    Authors
    Ahn, Hyo-Sung
    Ye, Mengbin
    Tran, Quoc Van
    Trinh, Minh Hoang
    Liu, Ji
    Moore, Kevin L
    Date
    2020
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Ahn, H.-S. and Ye, M. and Tran, Q.V. and Trinh, M.H. and Liu, J. and Moore, K.L. 2020. Opinion Dynamics With Cross-Coupling Topics: Modeling and Analysis. IEEE Transactions on Computational Social Systems.
    Source Title
    IEEE Transactions on Computational Social Systems
    DOI
    10.1109/TCSS.2020.2974899
    ISSN
    2329-924X
    Faculty
    Faculty of Science and Engineering
    School
    School of Elec Eng, Comp and Math Sci (EECMS)
    Remarks

    © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/78259
    Collection
    • Curtin Research Publications
    Abstract

    To model the cross couplings of multiple topics, we develop a set of rules for opinion updates of a group of agents. The rules are used to design or assign values to the elements of weighting matrices. The cooperative and anticooperative couplings are modeled in both the inverse-proportional and proportional structures. The behaviors of opinion dynamics are analyzed using a nullspace property of the state-dependent matrix-weighted Laplacian matrices and a Lyapunov candidate. Various consensus properties of the state-dependent matrix-weighted Laplacian matrices are predicted according to the interagent network topology and interdependent topical coupling topologies.

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