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Robustness Tests Replicate Corneille et al.’s (2020) Fake News by Repetition Effect Cover

Robustness Tests Replicate Corneille et al.’s (2020) Fake News by Repetition Effect

Open Access
|Oct 2022

Figures & Tables

irsp-35-683-g1.png
Figure 1

Proportions of ‘used as fake news on social media’ judgments as a function of Repetition (dashed horizontal line: no bias toward the ‘yes, fake news’ or the ‘no, not fake news’ side) and Factual truth in Experiment 1. The dots are participants’ scores (jittered). The error bars are the 95% confidence intervals, with the mean in between. The distributions are the kernel probability density of the data (trimmed to remain within the range of possible values, 0 to 1).

irsp-35-683-g2.png
Figure 2

Proportions of ‘yes’ judgments as a function of Repetition (dashed horizontal line: no bias toward the ‘yes’ or the ‘no’ side) and Judgment condition in Experiment 2. The dots are participants’ scores (jittered). The error bars are the 95% confidence intervals, with the mean in between. The distributions are the kernel probability density of the data (trimmed to remain within the range of possible values, 0 to 1).

DOI: https://doi.org/10.5334/irsp.683 | Journal eISSN: 2397-8570
Language: English
Submitted on: Jan 26, 2022
Accepted on: Aug 23, 2022
Published on: Oct 12, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Jérémy Béna, Olivier Corneille, Adrien Mierop, Christian Unkelbach, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.