Differences of Opinion

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Dionissi Aliprantis ;
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, PMLR 62:1-12, 2017.

Abstract

This paper considers the resolution of ambiguity according to the scientific ideal of direct observation when there is a practical necessity for social learning. An agent faces ambiguity when she directly observes low-quality data yielding set-identified signals. I suppose the agent’s objective is to choose the single belief replicating what would occur with high-quality data yielding point-identified signals. I allow the agent to solve this missing data problem using signals observed through her network in combination with a model of social learning. In some cases the agent’s belief formation reduces to DeGroot updating and beliefs in a network reach a consensus. In other cases the agent’s updating can generate polarization and sustain clustered disagreement, even on a connected network where everyone observes the same data and processes that data with the same model.

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