Abstract
There is growing worldwide concern that the rampant spread of digital fake news (DFN) via new media technologies is detrimentally impacting Democratic elections. However, the actual influence of this recent Internet phenomenon on electoral decisions has not been directly examined. Accordingly, this study tested the effects of attention to DFN on readers’ Presidential candidate preferences via an experimental web-survey administered to a cross-sectional American sample (N = 552). Results showed no main effect of exposure to DFN on participants’ candidate evaluations or vote choice. However, the perceived believability of DFN about the Democratic candidate negatively mediated evaluations of that candidate—especially amongst far-right ideologues. These results suggest that DFN may at worst reinforce the partisan dispositions of mostly politically conservative Internet users, but does not cause or induce conversions in these dispositions. Overall, this study contributes novel experimental evidence, indicating that the potential electoral impact of DFN, although concerning, is strongly conditional on a reciprocal interaction between message receptibility and a pre-existing right-wing ideological orientation. The said impact is, therefore, likely narrow in scope.
Highlights
Following the 2016 Presidential election victory of Donald Trump, several journalists and politicians argued that the widespread circulation of digital fake news (DFN) via new media technologies played a decisive role in influencing votes and turnout (Mustafaraj and Metaxas 2017; Tandoc et al 2017)
Analysis of covariance (ANCOVA) tests were conducted to examine the direct effects of DFN exposure on candidate evaluations and voter support (H1), with the measured demographic, mediator-moderator, and covariates entered as controls
The expected interaction between partisan ideology and perceived news believability on intentions to vote for Clinton was insignificant (B = − 0.001, bootstrap SE = 0.10; [confidence intervals (CLs)] = [− 0.2054, 0.2028], p = 0.99), as was the moderated-mediation index of 0.00 bootstrap SE = 0.07; with a 95% bootstrap [CL] = [− 0.1501, 0.1560]
Summary
Following the 2016 Presidential election victory of Donald Trump, several journalists and politicians argued that the widespread circulation of digital fake news (DFN) via new media technologies played a decisive role in influencing votes and turnout (Mustafaraj and Metaxas 2017; Tandoc et al 2017). This notion has been given further credence by accusations from American intelligence officials that the Russian government honed and sponsored a sophisticated bombardment of DFN through Facebook and Twitter to sway the election in Trump’s favor. While highly insightful, the few available scientific studies on DFN have mostly either only looked at the spread and usage of DFN during the 2016 US Presidential election (e.g., Guess et al 2018; Nelson and Taneja 2018), or examined factors that increase a reader’s receptivity to DFN messages (e.g., Allcott and Gentzkow 2017; Pennycook et al 2017)
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