Exploring Approaches to Low Fertility through Integrated Application of Big Data-based Topic Modeling and System Dynamics: The Case of South Korea
DOI:
https://doi.org/10.56294/dm2025852Keywords:
topic modelling, system dynamics, low fertility rate, integrated approachAbstract
This study examines the multidimensional aspects of low fertility by integrating big data text mining with system dynamics analysis. While previous research primarily utilized macroeconomic, big data discourse, or system dynamics approaches independently, this research combines textual big data analysis and causal loop modeling to address gaps identified in prior methodologies. Specifically, we analyze social discourses and sentiments related to low fertility through text mining of social media data, and then link these qualitative insights with quantitative simulations using system dynamics. Our integrated approach offers a novel methodological framework that enhances understanding of the complex interactions between societal perceptions, policy interventions, and demographic outcomes. The results underscore the importance of capturing both qualitative social trends and quantitative policy feedback loops, providing valuable implications for designing more effective fertility-enhancing policies.
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Copyright (c) 2025 Young-Chool Choi , Sanghyun Ju , Gyutae Lee , Sangkun Kim, Sungho Yun (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
