  Opinion Dynamics lacks a theoretical basis. In this article, I propose to use
a decision-theoretic framework, based on the updating of subjective
probabilities, as that basis. We will see we get a basic tool for a better
understanding of the interaction between the agents in Opinion Dynamics
problems and for creating new models. I will review the few existing
applications of Bayesian update rules to both discrete and continuous opinion
problems and show that several traditional models can be obtained as special
cases or approximations from these Bayesian models. The empirical basis and
useful properties of the framework will be discussed and examples of how the
framework can be used to describe different problems given.
