Back to Search Start Over

Optimizing consensus reaching in the hybrid opinion dynamics in a social network•.

Authors :
Liu, Yi
Liang, Haiming
Gao, Lei
Guo, Zhaoxia
Source :
Information Fusion. Aug2021, Vol. 72, p89-99. 11p.
Publication Year :
2021

Abstract

• We propose a consensus reaching strategy for social network hybrid opinion dynamics. • We present the hybrid opinion dynamics models in a social network. • We discuss the properties of the consensus reaching strategy. • We justify the effectiveness of the proposed consensus reaching strategy. Hybrid opinion dynamics which involves two types of individuals (i.e., leaders and followers) communicate in real time and share opinions and knowledge have been widely used in diverse applications. In real applications of hybrid opinion dynamics, one of the main demands is how to manage a consensus among individuals. This paper aims at proposing a novel consensus reaching strategy for the hybrid opinion dynamics in a social network. Firstly, we give the network partition algorithm to divide the social network into sub-network, and introduce Floyd algorithm to calculate the shortest path between any two individuals, which can provide the assistance for determining the weights among individuals. On this basis, we present the hybrid opinion dynamics model. Next, we develop the consensus reaching model with minimum adjustments (i.e. CRMD model) in hybrid opinion dynamics, and discuss some the properties of the CRMD model. Furthermore, the detailed numerical and simulation analysis are conducted to illustrate the effectiveness of this CRMD model. The simulation results show the CRMD model has the distinct advantages over other consensus strategies. Thus, the CRMD model is helpful to manage and control the public opinions for the government and enterprise. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15662535
Volume :
72
Database :
Academic Search Index
Journal :
Information Fusion
Publication Type :
Academic Journal
Accession number :
149804271
Full Text :
https://doi.org/10.1016/j.inffus.2021.02.018