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Opinion Dynamics With Cross-Coupling Topics: Modeling and Analysis

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Open access
Authors
Ahn, Hyo-Sung
Ye, Mengbin
Tran, Quoc Van
Trinh, Minh Hoang
Liu, Ji
Moore, Kevin L
Date
2020
Type
Journal Article

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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
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Faculty
Faculty of Science and Engineering
School
School of Elec Eng, Comp and Math Sci (EECMS)
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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.