The (minimal) persuasive advantage of political video over text.


Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
23 11 2021
Historique:
accepted: 08 10 2021
entrez: 16 11 2021
pubmed: 17 11 2021
medline: 22 12 2021
Statut: ppublish

Résumé

Concerns about video-based political persuasion are prevalent in both popular and academic circles, predicated on the assumption that video is more compelling than text. To date, however, this assumption remains largely untested in the political domain. Here, we provide such a test. We begin by drawing a theoretical distinction between two dimensions for which video might be more efficacious than text: 1) one's belief that a depicted event actually occurred and 2) the extent to which one's attitudes and behavior are changed. We test this model across two high-powered survey experiments varying exposure to politically persuasive messaging (total

Identifiants

pubmed: 34782473
pii: 2114388118
doi: 10.1073/pnas.2114388118
pmc: PMC8617416
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2021 the Author(s). Published by PNAS.

Déclaration de conflit d'intérêts

The authors declare no competing interest.

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Auteurs

Chloe Wittenberg (C)

Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA 02139; cwitten@mit.edu.

Ben M Tappin (BM)

Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA 02139.
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02142.

Adam J Berinsky (AJ)

Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA 02139.

David G Rand (DG)

Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02142.
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.

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Classifications MeSH