Artificial intelligence-enhanced evaluation of blepharoplasty content on social media: A cross-sectional study

Objectives: Blepharoplasty is the most commonly performed facial esthetic procedure in the US, with increasing patient reliance on social media platforms for surgical information. The quality, accuracy, and engagement dynamics of blepharoplasty-related content remain poorly characterized. Material and Methods: This cross-sectional study analyzed 140 TikTok videos under the hashtag #Blepharoplasty (August 12–13, 2025). Videos were categorized by creator type, content theme, and engagement metrics (likes, comments, shares). Informational quality was assessed using the global quality scale (GQS) and modified DISCERN (mDISCERN) tools through dual human review and artificial intelligence (AI)-assisted scoring. High engagement was defined as ≥15,000 likes and ≥900 shares (upper 25 th percentile). Sentiment analysis of 1,337 comments was performed by two independent reviewers and validated by AI. Results: Patients (47%) and surgeons (44%) were the predominant content creators, with post-operative experience (41%) being the most frequent category. Median engagement included 2,385 likes, 168 shares, and 94 comments per video. Overall content quality was low (median GQS: 2; median mDISCERN: 1–2). Highly liked and highly shared videos demonstrated significantly greater interaction ( P < 0.001) but lower mDISCERN scores ( p = 0.012–0.041). Sentiment analysis revealed that AI classified more comments as positive (42%) and negative (15%) compared to human reviewers (38–39% positive; 8–12% negative). Inter-rater reliability between human reviewers was substantial (k = 0.747). Conclusion: Blepharoplasty-related content on TikTok demonstrates high engagement but low informational quality. High-performing videos prioritize engagement over reliability, underscoring the need for surgeon-led, evidence-based content to improve patient education and mitigate misinformation.