The marital and fertility sentiment orientation of Chinese women and its influencing factors - An analysis based on natural language processing
Document Type
Article
Publication Date
2-1-2024
Abstract
Background With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend the fundamental reasons behind these attitude changes and to provide a basis for targeted policymaking, this study employs natural language processing techniques to analyze the discourse of Chinese women.Methods The study focused on analyzing 3,200 comments from Weibo, concentrating on six prominent topics linked to women's marriage and fertility. These topics were treated as research cases. The research employed natural language processing techniques, such as sentiment orientation analysis, Word2Vec, and TextRank.Results Firstly, the overall sentiment orientation of Chinese women toward marriage and fertility was largely pessimistic. Secondly, the factors contributing to this negative sentiment were categorized into four dimensions: social policies and rights protection, concerns related to parenting, values and beliefs associated with marriage and fertility, and family and societal culture.Conclusion Based on these outcomes, the study proposed a range of mechanisms and pathways to enhance women's sentiment orientation towards marriage and fertility. These mechanisms encompass safeguarding women and children's rights, promoting parenting education, providing positive guidance on social media, and cultivating a diverse and inclusive social and cultural environment. The objective is to offer precise and comprehensive reference points for the formulation of policies that align more effectively with practical needs.
Keywords
Marital, fertility, Chinese women, influencing factors, natural language processing
Divisions
ai,Anthropology
Funders
China Postdoctoral Science Foundation (2023M730772)
Publication Title
PLoS ONE
Volume
19
Issue
2
Publisher
Public Library of Science
Publisher Location
1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA