The Liar's Dividend: The Impact of Deepfakes and Fake News on Trust in Political Discourse

Kaylyn Jackson Schiff, Daniel S. Schiff and Natalia Bueno
Additional contact information
Kaylyn Jackson Schiff: Emory University
Daniel S. Schiff: Purdue University

No x43ph, SocArXiv from Center for Open Science

Abstract: This study examines the phenomenon of misinformation about misinformation, or politicians falsely claiming that stories are fake news or deepfakes. Strategic and false claims that stories are fake news or deepfakes may benefit politicians by helping them maintain support after a scandal. We propose that this benefit, known as the "liar's dividend," may be achieved through two strategies employed by politicians: by invoking informational uncertainty or by rallying core supporters in opposition. We administer five survey experiments to over 15,000American adults detailing hypothetical politician responses to video or text news stories depicting real politician scandals. We find that claims of misinformation representing both strategies increase politician support across partisan subgroups. These strategies are effective against text-based reports of scandals but are largely ineffective against video evidence and do not reduce general trust in media. Finally, these false claims produce greater dividends for politicians than alternative responses to scandal, such as remaining silent or apologizing.

Date: 2023-08-10
New Economics Papers: this item is included in nep-pol and nep-soc
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://osf.io/download/64d228b4a2be6b59fa314730/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:x43ph

DOI: 10.31219/osf.io/x43ph

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().