Literature DB >> 26331572

The Appeal to Expert Opinion: Quantitative Support for a Bayesian Network Approach.

Adam J L Harris1, Ulrike Hahn2, Jens K Madsen2, Anne S Hsu3.   

Abstract

The appeal to expert opinion is an argument form that uses the verdict of an expert to support a position or hypothesis. A previous scheme-based treatment of the argument form is formalized within a Bayesian network that is able to capture the critical aspects of the argument form, including the central considerations of the expert's expertise and trustworthiness. We propose this as an appropriate normative framework for the argument form, enabling the development and testing of quantitative predictions as to how people evaluate this argument, suggesting that such an approach might be beneficial to argumentation research generally. We subsequently present two experiments as an example of the potential for future research in this vein, demonstrating that participants' quantitative ratings of the convincingness of a proposition that has been supported with an appeal to expert opinion were broadly consistent with the predictions of the Bayesian model.
Copyright © 2015 Cognitive Science Society, Inc.

Entities:  

Keywords:  Appeal to authority; Appeal to expert opinion; Argumentation; Bayesian probability; Epistemic authority; Quantitative modeling

Mesh:

Year:  2015        PMID: 26331572     DOI: 10.1111/cogs.12276

Source DB:  PubMed          Journal:  Cogn Sci        ISSN: 0364-0213


  7 in total

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Authors:  Suzanne Hoogeveen; Julia M Haaf; Joseph A Bulbulia; Robert M Ross; Ryan McKay; Sacha Altay; Theiss Bendixen; Renatas Berniūnas; Arik Cheshin; Claudio Gentili; Raluca Georgescu; Will M Gervais; Kristin Hagel; Christopher Kavanagh; Neil Levy; Alejandra Neely; Lin Qiu; André Rabelo; Jonathan E Ramsay; Bastiaan T Rutjens; Hugh Turpin; Filip Uzarevic; Robin Wuyts; Dimitris Xygalatas; Michiel van Elk
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3.  The effects of recursive communication dynamics on belief updating.

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Journal:  Proc Biol Sci       Date:  2020-07-22       Impact factor: 5.349

4.  The Bi-directional Relationship between Source Characteristics and Message Content.

Authors:  Peter J Collins; Ulrike Hahn; Ylva von Gerber; Erik J Olsson
Journal:  Front Psychol       Date:  2018-01-30

5.  The Impact Factor Fallacy.

Authors:  Frieder M Paulus; Nicole Cruz; Sören Krach
Journal:  Front Psychol       Date:  2018-08-20

6.  Deconstructing the Conspiratorial Mind: the Computational Logic Behind Conspiracy Theories.

Authors:  Francesco Rigoli
Journal:  Rev Philos Psychol       Date:  2022-08-27

7.  A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle.

Authors:  Jens Koed Madsen; Toby D Pilditch
Journal:  PLoS One       Date:  2018-04-10       Impact factor: 3.240

  7 in total

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