Back to Search
Start Over
Fake news and its electoral consequences: a survey experiment on Mexico.
- Source :
- AI & Society; Jun2024, Vol. 39 Issue 3, p1065-1078, 14p
- Publication Year :
- 2024
-
Abstract
- This study examined the effect of fake news on electoral outcome. Using post-election surveys, previous studies found associations between exposure to fake news and voting behavior, though these observational studies failed to show that these changes were actually caused by fake news. To examine whether fake news really affects voting behavior, we need to experimentally manipulate voters' exposure to fake news in real elections and see if voters regret their vote choice knowing that the information was false. For this purpose, our study focused on Mexico's 2018 presidential election, which provided an ideal setting. During the campaign, false information about a scandal allegedly involving Ricardo Anaya, a candidate from the National Action Party, was widely disseminated. However, his innocence was officially acknowledged after the election. Using this correction of fake news as a treatment, we tested a sample of 1,561 individuals to assess whether the retraction of fake news caused post-election regret: would Mexican voters have voted differently if they had not been exposed to such false information. Our multivariate analyses found that the retraction of fake news did cause post-election regret among voters with lower internal political efficacy, but voters associated with higher political knowledge and internal political efficacy were not affected by the retraction and were less likely to experience regret. About 20% of the respondents (N = 168) experienced post-election regret, and of those, about 35% would have switched their vote to Anaya. The findings corroborate lasting effects of fake news, which may have non-negligible effects on electoral outcomes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09515666
- Volume :
- 39
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- AI & Society
- Publication Type :
- Academic Journal
- Accession number :
- 178149857
- Full Text :
- https://doi.org/10.1007/s00146-022-01541-9