The “multiple exposure effect” (MEE): How multiple exposures to similarly biased online content can cause increasingly larger shifts in opinions and voting preferences

Abstract

In three randomized, controlled experiments performed on simulations of three popular online platforms – Google search, X/Twitter, and Alexa – with a total of 1,488 undecided, eligible US voters, we asked whether multiple exposures to similarly biased content on those platforms could shift opinions and voting preferences more than a single exposure could. All participants were first shown brief biographies of two political candidates, then asked about their voting preferences, then exposed to biased content on one of our three simulated platforms, and then asked again about their voting preferences. In all experiments, participants in different groups saw biased content favoring one candidate, his or her opponent, or neither. In all the experiments, our primary dependent variable was Vote Manipulation Power (VMP), the percentage increase in the number of participants inclined to vote for one candidate after having viewed content favoring that candidate. In Experiment 1 (on our Google simulator), the VMP increased with successive searches from 14.3% to 20.2% to 22.6%. In Experiment 2 (on our X/Twitter simulator), the VMP increased with successive exposures to biased tweets from 49.7% to 61.8% to 69.1%. In Experiment 3 (on our Alexa simulator), the VMP increased with successive exposures to biased replies from 72.1% to 91.2% to 98.6%. Corresponding shifts were also generally found for how much participants reported liking and trusting the candidates and for participants’ overall impression of the candidates. Because multiple exposures to similarly biased content might be common on the internet, we conclude that our previous reports about the possible impact of biased content – always based on single exposures – might have underestimated its possible impact. Findings in our new experiments exemplify what we call the “multiple exposure effect” (MEE).