Leveraging Artificial Intelligence to Appraise Social Media Narratives on Breast Reduction Procedures: A Snapshot Analysis

Background: Social media platforms increasingly influence patient perceptions regarding reconstructive procedures.This study evaluated the characteristics, quality, engagement patterns, and user sentiment associated with breast reduction-related content on TikTok, while assessing the performance of artificial intelligence (AI) in content and sentiment analysis.Methods: A cross-sectional analysis of 140 TikTok videos on breast reduction was conducted.Engagement metrics, including likes, comments, shares, saves, and a weighted engagement index, were collected.The modified DISCERN (mDISCERN) and Global Quality Scale (GQS) were used to appraise content quality by AI and two human reviewers.Sentiment analysis was performed by human reviewers, ChatGPT, and Claude AI.High-engagement videos were defined as those within the upper quartile for likes (≥30,400) or shares (≥1,050).Results: Most videos were created by patients (89%) and focused on postoperative experiences (75%).Videos demonstrated substantial engagement, with median values of 3,860.5 likes, 131 comments, and 194.5 shares.Overall informational quality was poor, with median GQS and mDISCERN scores of 1-2 across raters.Highly liked and highly shared videos were significantly shorter in duration (18 vs. 34 seconds; p < 0.05) and generated markedly greater engagement across all metrics.Popular videos received significantly lower quality scores from human reviewers.Sentiment analysis revealed predominantly positive responses (49-58%).Claude showed greater concordance with human consensus than ChatGPT (κ = 0.749 vs. 0.649).Conclusion: Breast reduction content on TikTok is largely patient-driven and characterized by high engagement but low informational quality.Shorter videos achieved greater dissemination despite being associated with less reliable health information.