Cross-Platform UGC Text Analysis on Fertility Topics in Chinese Society: Themes and Sentiments

As China’s demographic transition deepens and fertility rates continue to decline, childbearing has shifted from a private family matter to a salient public issue. Social media platforms have become key arenas in which fertility-related concerns are articulated, negotiated, and publicly constructed. This study analyzes fertility-related user-generated content (UGC) from three major Chinese platforms—Sina Weibo, Douyin, and Toutiao—collected between 30 June and 31 December 2024. Using BERTopic-based topic modeling, sentiment quantification, and cross-platform comparison, the study examines how fertility discourse is thematically organized and emotionally expressed across different platform environments. The results reveal clear platform differentiation. Douyin primarily foregrounds individualized and relational narratives embedded in everyday family life, Toutiao emphasizes gender-neutral, macro-social and policy-oriented interpretations, while Sina Weibo centers on gender relations, institutional arrangements, and rights-based debate. Sentiment analysis indicates that fertility discourse on all three platforms exhibits an overall negative emotional orientation, though with varying intensity. Rather than reflecting uniformly pessimistic fertility attitudes, this negative bias is interpreted as a product of platformized public discourse. The study proposes an emotional filtering mechanism to explain how fertility-related emotions are selectively distributed across communicative spaces: problem-oriented and conflict-laden expressions are more likely to gain visibility in open public platforms. By integrating a platformization perspective, this study demonstrates how platform-specific communication logics shape both the thematic configuration and emotional structure of fertility discourse, offering new insights into the mediated construction of fertility concerns in contemporary China.