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The Appeal to Expert Opinion: Quantitative Support for a Bayesian Network Approach
Adam J L Harris1, Ulrike Hahn2, Jens K Madsen2
1Department of Experimental Psychology, University College, London.
Cognitive Science
|September 3, 2015
Summary
This study formalizes the appeal to expert opinion using a Bayesian network, providing a framework to predict how people evaluate expert testimony. Experimental results align with the model, supporting its utility in argumentation research.
Area of Science:
- Cognitive Science
- Argumentation Theory
- Bayesian Modeling
Background:
- The appeal to expert opinion is a common argument form.
- Previous treatments often lack quantitative rigor.
- Evaluating expert testimony involves assessing expertise and trustworthiness.
Purpose of the Study:
- To develop a normative Bayesian framework for the argument from expert opinion.
- To enable quantitative predictions of how individuals evaluate expert testimony.
- To test the framework's predictions experimentally.
Main Methods:
- Formalization of the argument from expert opinion within a Bayesian network.
- Development of a model incorporating expert expertise and trustworthiness.
- Conducting two experiments to gather quantitative ratings of argument convincingness.
Main Results:
- Participants' ratings of expert opinion arguments were broadly consistent with the Bayesian model's predictions.
- The proposed framework successfully captures critical aspects of evaluating expert testimony.
- Experimental data supports the quantitative predictions of the Bayesian model.
Conclusions:
- The Bayesian network provides a suitable normative framework for the argument from expert opinion.
- This approach offers a beneficial methodology for argumentation research.
- Future research can leverage this framework for quantitative analysis of persuasive arguments.
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