Exploring Women’s Fertility Perspectives Through AI-Assisted Qualitative Text Analysis: Evidence from Chinese Social Media

DOI

10.2991/978-2-38476-611-6_87How to use a DOI?

Keywords

Women’s fertility perspectives; AI-assisted text analysis; Social media; Low fertility; Digital discourse

Abstract

Against the backdrop of China’s low fertility rate, issues related to female reproduction have become increasingly prominent. To answer this research question, this study used China’s social media data and AI-assisted qualitative text analysis to reveal women’s perspectives on fertility issues against the backdrop of low birth rates. By integrating AI-assisted topic clustering analysis with researcher-led qualitative interpretation, the study captured the mainstream viewpoints emerging from online discussions on themes such as fertility, motherhood, family, and personal life. The findings indicate that economic pressure, work-family conflicts, and personal choices constitute the three core themes associated with contemporary women’s fertility perspectives. These thematic analyses reveal that fertility decisions are not only closely linked to structural issues such as housing costs, employment disparities, and unequal parenting burdens, but also intertwined with shifts in social values including personal autonomy, self-development, and emotional health. By integrating AI-assisted thematic analysis with qualitative interpretation, this study further demonstrates the potential of digital social media data in examining the construction of fertility-related meanings within online environments.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 International License (http://creativecommons.org/licenses/by-nc/3.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Dan He
PY  - 2026
DA  - 2026/09/07
TI  - Exploring Women’s Fertility Perspectives Through AI-Assisted Qualitative Text Analysis: Evidence from Chinese Social Media
BT  - Proceedings of the 2026 12th International Conference on Digital Humanities and Frontiers in Social Sciences (DHFSS 2026)
PB  - Atlantis Press
SP  - 801
EP  - 808
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-611-6_87
DO  - 10.2991/978-2-38476-611-6_87
ID  - He2026
ER  -