MyJournals Home  

RSS FeedsEntropy, Vol. 24, Pages 1112: Dynamic Parameter Calibration Framework for Opinion Dynamics Models (Entropy)

 
 

12 august 2022 13:10:18

 
Entropy, Vol. 24, Pages 1112: Dynamic Parameter Calibration Framework for Opinion Dynamics Models (Entropy)
 


In the past decade, various opinion dynamics models have been built to depict the evolutionary mechanism of opinions and use them to predict trends in public opinion. However, model-based predictions alone cannot eliminate the deviation caused by unforeseeable external factors, nor can they reduce the impact of the accumulated random error over time. To solve this problem, we propose a dynamic framework that combines a genetic algorithm and a particle filter algorithm to dynamically calibrate the parameters of the opinion dynamics model. First, we design a fitness function in accordance with public opinion and search for a set of model parameters that best match the initial observation. Second, with successive observations, we tracked the state of the opinion dynamic system by the average distribution of particles. We tested the framework by using several typical opinion dynamics models. The results demonstrate that the proposed method can dynamically calibrate the parameters of the opinion dynamics model to predict public opinion more accurately.


 
101 viewsCategory: Informatics, Physics
 
Entropy, Vol. 24, Pages 1113: Monte Carlo Simulation of Stochastic Differential Equation to Study Information Geometry (Entropy)
Entropy, Vol. 24, Pages 1114: Quantum Teleportation and Dense Coding in Multiple Bosonic Reservoirs (Entropy)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten