ArticlePloS one2025
The Multiple Platforms Effect (MPE): A quantification of how exposure to similarly biased content on multiple online platforms might impact users.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past decade, controlled studies have identified nearly a dozen new forms of manipulation that can be used by search engines, social media platforms, microblogging platforms, and intelligent personal assistants. A recent study has shown that when users were exposed repeatedly to similarly biased content on the same platform, the net impact of those exposures was additive. We now ask the following: What happens when users are exposed to similarly biased content generated by different means on multiple online platforms? In the present experiment, which was randomized, controlled, counterbalanced, and double-blind, we exposed people to similarly biased content generated by different means on three different platforms - simulations of Google Search, Alexa, and X (f.k.a., Twitter) - presented successively and in a random order. We found that the impact of successive exposures was additive for both opinions and voting preferences pertaining to political candidates. Overall, the number of undecided voters voting for the favored candidate increased with each successive platform exposure by 42.4%, then 56.5%, then 66.7% over the pre-exposure level. We speculate that if Big Tech companies share values or political preferences, their net effect on our elections might be considerably greater than the effect of any individual company.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.