Infertility-related trends and thematic transitions on Chinese social media: A longitudinal topic modeling analysis

Objective This study examines shifting trends in infertility-related concerns among Sina Weibo users by comparing data from 2018 (pre-pandemic) and 2023 (post-pandemic). The goal is to provide evidence-based insights to inform targeted health education and digital information strategies. Methods Utilizing web crawler technology, Weibo posts tagged with #infertility# were harvested for the years 2018 and 2023. A hybrid methodological approach was employed: “High-Attention” posts were categorized via manual coding, while “Low-Attention” posts were analyzed using Latent Dirichlet Allocation (LDA) topic modeling. Results High-Attention posts in both periods were characterized by four primary orientations: Policy and News, Medical Science Popularization, Personal Sharing, and Solely Commercial. In 2018, the implicit hotspots centered on outpatient appointment consultations, the integration of traditional Chinese and Western medicine, and etiology screening. By 2023, the focus of implicit hotspots shifted toward spiritual practices and body conditioning, alongside a burgeoning interest in IVF technology and international medical trends. Conclusion This study demonstrates that combining manual content analysis with LDA topic modeling is an effective framework for longitudinal monitoring of health discourse on social media. These findings elucidate evolving public concerns and engagement patterns over time, offering a valuable reference for health informatics research and public health policy monitoring.