Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 26, 2026
Date Accepted: Aug 13, 2026
How Human Papillomavirus Vaccine-Related Social Media Content Has Been Studied Across Eight Social Media Platforms: A Scoping Review of Communication Content, Information Sources, and Analytical Approaches
ABSTRACT
Background:
Social media has become an important channel for health information dissemination and public discussion of human papillomavirus (HPV) vaccination. Although previous reviews have examined social media and HPV vaccination, many focused on single platforms, broader HPV-related topics, or potential effects on knowledge. A recent cross-platform synthesis specifically focused on HPV vaccine-related communication content, information sources, and analytical approaches remains limited. Objectives: This scoping review aimed to map and synthesize peer-reviewed studies examining HPV vaccine-related social media content, with particular attention to communication content, information sources, and methodological characteristics.
Methods:
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, we searched PubMed, Web of Science, MEDLINE, Embase, and Scopus, with the final search performed on June 10, 2026. We included peer-reviewed English-language original studies published between 2006 and 2025 that analyzed HPV vaccine-related communication content on social media. Data were charted using a structured extraction form and synthesized descriptively. No formal risk-of-bias assessment was conducted.
Results:
A total of 46 studies published between 2012 and 2025 met the eligibility criteria. Eight social media platforms were represented, with X most frequently studied, followed by Weibo. HPV vaccine-related communication was synthesized into five recurring content types: risk- and concern-oriented, benefit- and prevention-oriented, misinformation- or distrust-related, experiential and narrative communication, and practical and policy-related communication. Across studies, prevention and benefit messages coexisted with safety concerns, side effects, access barriers, misinformation, distrust, and personal narratives. Personal accounts were often associated with experiential narratives or negative sentiment, whereas professionals were less common but generally provided more informational or higher-quality content. Analytical approaches included content analysis, sentiment analysis, topic modeling, and network analysis, but theoretical frameworks were applied only in a minority of studies. Discussion: The evidence was limited by heterogeneity in platforms, sampling strategies, data collection periods, coding schemes, and analytical methods, limiting direct comparison across studies. Because most studies analyzed publicly available social media content, this review could not determine individual-level exposure, interpretation, vaccination intention, or vaccine uptake. Overall, HPV vaccine discourse cannot be adequately understood through sentiment polarity alone.
Conclusions:
This review provides a cross-platform, content-focused synthesis of how HPV vaccine-related social media communication has been studied. Unlike previous reviews focused mainly on single platforms, broader HPV-related social media research, or potential effects of social media on vaccine knowledge and attitudes, this review clarifies how HPV vaccine-related content has been described, who generates it, and which methods have been used to analyze it. These findings support theory-informed, platform-sensitive research and may inform public health communication strategies, including evidence-based education, transparent risk communication, credible source engagement, narrative-informed messaging, misinformation monitoring, and improved information quality. Funding: This work was supported by the Waseda University Grants for Special Research Projects (No. 2025C-575 and No. 2026C-216). Registration: The protocol was prospectively registered with the Open Science Framework (OSF, https://osf.io/zrtdf).
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