Randomized volunteer intervention reduced comments and reaction on anti-COVID-19 vaccine posts on Facebook

Social correction has been shown to be effective in reducing misperceptions and limiting the production of harmful content online, but most current evidence comes from platform-run systems or controlled experiments. We evaluate a volunteer-led intervention on Facebook in which trained healthcare workers replied to COVID-19 vaccine-related posts and comments. The intervention used two sources of random variation: randomized ordering of posts on volunteers’ worklists and random assignment of whether drafted replies were posted. We estimate effects on post-level engagement metrics, distinguishing diffusion indicators, measured by shares; interaction indicators, measured by comments; and affective indicators, measured by likes and reactions. The intervention reduced comments on treated posts, with broader declines in some affective responses in randomized-treatment analyses, especially for newer posts and posts classified as anti-vaccine. We find little evidence of reduced sharing. Our results indicate changes in some forms of engagement with treated posts; they do not directly demonstrate reductions in misinformation prevalence, belief change, or exposure patterns.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-08-20
DOI
https://doi.org/10.1038/s41598-026-62919-z
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Randomized volunteer intervention reduced comments and reaction on anti-COVID-19 vaccine posts on Facebook

Kirsten Cornelson, Theresa Tang, Margaret Pateman, Caitlin Ford et al.
Scientific Reports
Misinformation and Its Impacts
article

Randomized volunteer intervention reduced comments and reaction on anti-COVID-19 vaccine posts on Facebook

Kirsten Cornelson, Theresa Tang, Margaret Pateman, Caitlin Ford, Hinna Hasan, Janette Wong, Hao Chen, Jia Hu, Madison Fullerton
article en

Abstract

Social correction has been shown to be effective in reducing misperceptions and limiting the production of harmful content online, but most current evidence comes from platform-run systems or controlled experiments. We evaluate a volunteer-led intervention on Facebook in which trained healthcare workers replied to COVID-19 vaccine-related posts and comments. The intervention used two sources of random variation: randomized ordering of posts on volunteers’ worklists and random assignment of whether drafted replies were posted. We estimate effects on post-level engagement metrics, distinguishing diffusion indicators, measured by shares; interaction indicators, measured by comments; and affective indicators, measured by likes and reactions. The intervention reduced comments on treated posts, with broader declines in some affective responses in randomized-treatment analyses, especially for newer posts and posts classified as anti-vaccine. We find little evidence of reduced sharing. Our results indicate changes in some forms of engagement with treated posts; they do not directly demonstrate reductions in misinformation prevalence, belief change, or exposure patterns.

Scientific Reports
Western University (CA), University of Calgary (CA), Zero Emissions Resource Organisation (NO), Ivey Business School, University of Guelph (CA), McMaster University (CA)
Merck Canada
Openalex Percentile: Top 4%
Misinformation and Its Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.