Leveraging Text Mining and Network Analysis for the Diffusion of Agricultural Science and Technology Policies in China

Xiaohe Liang, Yu Wu, Jiajia Liu, Jiayu Zhuang, Tong Yuan, Ying Chen, Lizhen Cui, Ailian Zhou (), Jiajia Zhou () and Tong Li
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Xiaohe Liang: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Yu Wu: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jiajia Liu: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jiayu Zhuang: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Tong Yuan: Agricultural Trade Promotion Center, Minister of Agriculture and Rural Affairs, Beijing 100125, China
Ying Chen: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Lizhen Cui: College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Ailian Zhou: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jiajia Zhou: Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Tong Li: School of Agriculture and Food Sustainability, The University of Queensland, St Lucia, QLD 4072, Australia

Agriculture, 2025, vol. 15, issue 9, 1-26

Abstract: Agricultural science and technology policies (ASTPs) have played a pivotal role in shaping agricultural innovation, sustainability, and cleaner production practices. Understanding how ASTPs diffuse is essential for optimizing policy design and advancing the green transition in agriculture. This study aims to investigate the diffusion of ASTPs in China, using a quantitative citation-based approach. The goal is to explore diffusion patterns, topic characteristics, and historical trajectories of ASTPs, thereby providing insights into policy transmission mechanisms that can inform future policy improvements. We analyze 3207 ASTP documents, focusing on policy citation links to examine the distribution, diffusion characteristics, and dynamics of policies. The analysis includes tracking topic evolution and identifying key policies while estimating the main diffusion paths. The results show that the top-down diffusion model is the dominant pattern of policy transmission, exhibiting the highest diffusion speed and both short- and long-term impacts. ASTPs have progressively expanded toward industrialization, informatization, and green development, with increased policy transmission efficiency. The diffusion process has formed three primary pathways: (i) enhancing agricultural innovation capacity, (ii) accelerating the transformation of technological achievements, and (iii) improving the agricultural science and technology innovation system. These pathways are critical to advancing sustainable and cleaner agricultural production. This study provides valuable insights into the diffusion of ASTPs and highlights key pathways for policy optimization. The findings suggest that enhancing policy frameworks and improving policy implementation efficiency will be crucial for facilitating the transition toward sustainable, low-carbon, and environmentally friendly agricultural practices. Future research should refine data sources and incorporate semantic analysis to capture more detailed policy transmission mechanisms.

Keywords: quantitative citation-based; agricultural science and technology; policy diffusion; diffusion model; diffusion pathways (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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