Crowd‑based user judgements against misinformation

This experiment investigates whether crowd-based content veracity judgements can be an efficient way to identify misinformation (Kim et al., 2019; Pennycook et al., 2019). We hypothesize that when false information is judged by subgroups of susceptible, like-minded people – as they would be found in so called echo chambers (Del Vicario et al., 2016; Vosoughi et al., 2018) – biased judgements can grant false information with the necessary early support to later convince other, initially skeptical members of a group. Conversely, we expect that when skeptical and susceptible individuals judge the veracity of a message in an alternating order while being informed about others’ previous judgements, the community provides checks-and-balances that increase subjects’ propensity to correctly identify true and false messages. The complete registration, including a description of the study design, the hypotheses and the analysis is outlined in the attached document. To this day (08-17-2021), no experimental data has been collected yet.