Currently submitted to: Journal of Medical Internet Research
Date Submitted: Nov 26, 2025
Open Peer Review Period: Nov 27, 2025 - Jan 22, 2026
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Engagement Trends in Online Vaccine Content: A Longitudinal YouTube Study
ABSTRACT
Background:
YouTube is the primary global video platform, hosting both authoritative health information and vaccine-skeptic viewpoints. However, engagement dynamics remain poorly understood.
Objective:
The aim of this study was to reveal the temporal and textual dynamics of engagement of the YouTube viewership with vaccination content, and specifically, content that is in favor of or against vaccination. We contextualized these dynamics in the authority signals of the posting channel and the moderation actions taken by the platform.
Methods:
We conducted a 6-month daily longitudinal analysis of 7,213 vaccine-related YouTube videos (November 2024 – May 2025) mentioning vaccination. We used zero-shot LLM classification with manual verification to classify the video stance toward vaccination, and the stance of their comments toward the video. The engagement and disagreement dynamics were modeled using Bayesian regression.
Results:
Our findings reveal a stark engagement asymmetry between content in support of or hesitant about vaccination, with the hesitant content receiving 10-fold higher engagement rates and reaching saturation 44% faster. Comment analysis revealed vaccine-hesitant videos foster echo chambers, while pro-vaccine content attracts battlegrounds. Considering the sources of vaccine-related content, pro-vaccine content tends to originate from organizations, particularly news and health institutions, while vaccine-hesitant discourse is more likely to come from individual creators, even those self-identifying as medical doctors. Moderation, in the rare occasion when it occurs (about 2% of the videos were taken down), comes after engagement saturation, limiting its effectiveness.
Conclusions:
Vaccine-hesitant content dominates YouTube’s engagement ecosystem through rapid early-stage amplification, which has direct implications for public health intervention timing and platform governance policy.
Citation
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