| dc.description.abstract | In the two years since the emergence of the new coronavirus, the world has seen a
proliferation of misinformation on social media. It was spread even by government officials
(the US president recommended drinking bleach) and health professionals (certain medical
doctors claimed that the vaccine against COVID-19 leads to infertility). Misinformation in
the pandemic is especially troubling as it can directly impact behavior and have detrimental
effects on public health. Typical social media platforms’ response to this upsurge was to
focus on discrediting the content, either by flagging it as fake or by debunking the false
information with facts. We wanted to test the efficacy of these content-based interventions in
a single design and added a third one aimed at debunking the misinformation by discrediting
its source (e.g. by pointing to their vested interest). We first exposed all participants (N=206)
to three pieces of fictitious news - about a new miracle cure Bamlanivimab, death in a
vaccine trial, and the efficacy of colloidal silver in combating the virus. Depending on the
experimental group, the news was then countered with either flagging, debunking, or source
questioning. We measured the interventions’ effects on the perceived accuracy of the news,
willingness to share it on social media, and to discuss it with friends; we assessed all three
dependent variables before and after the interventions. Our results indicate that corrections of
misinformation, regardless of their type, affected belief in the accuracy of misinformation.
The participants believed in misinformation less after the corrections were presented, in the
case of news regarding death in a vaccine trial (F(1) = 8.98, p < .01, η² = .04, M1-M2 = .65)
and a new miracle cure (F(1) = 11.84, p<.01, η² = .055, M1-M2 = .71). The effects of the
corrections, regardless of their type, on the willingness to share news on social media were
found, albeit inconsistently. Participants were less willing to share a piece of news regarding
Bamlanivimab on social media after correction (F(1) = 7.68, p < .01, η² = .036, M1-M2 =
.36), but more willing to share the one about death in a vaccine trial (F(1) = 9.20, p < .01, η²
= .043, M1-M2 = -.43), contrary to our predictions. Corrections did not affect the willingness
to share misinformation with friends, and there was no statistically significant difference
between the three types of corrections in their efficacy. We offer potential methodological
improvements for future research and discuss implications for public communication. | sr |
