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To see how this idea might apply in practice, consider a simple urn model of opinion polling to predict which of two candidates will win an election.
This paper suggests a discrete-time, non-linear, and time-variant model of opinion formation in a social network with global interactions.
In this paper, we suggest a new rule governing the process of belief updating to build a non-linear and non-stationary model of opinion dynamics.
This paper develops a discrete-time, non-linear, and time-variant model of opinion formation in a social network with global interactions to investigate the relationship between the final consensus belief and the set of agents' initial opinions.
Starting from [10], where the first model of opinion dynamics in a probabilistic framework was presented, opinion dynamics models were designed by using an analogy with the Ising model in statistical mechanics [11 13].
We study the theoretical properties of a boundedly rational model of opinion formation in which individuals aggregate the information they receive from their neighbors by using weights that are a function of neighbors' indegree.
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In contrary, informational Influence is one of the main underlying premises used by many well-known theoretical models of opinion dynamics.
A class of models of opinion formation based on the concept of cellular automata and the theory of social impact is studied, in particular the case when a strong leader and external impact are present.
For scale-free networks, with an exponent of the degree distribution
In this article, we describe a parallel agent-based model of spatial opinion diffusion that is driven by graphics processing units (GPUs).
However, in recent decades, advances in the field of information technology, and in telecommunications technology in particular, have led to the development of a new model of second opinion and the creation of the concept of telemedicine.
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CEO of Professional Science Editing for Scientists @ prosciediting.com