基于LDA模型的中国智慧农业政策文本量化分析

Quantitative Analysis of Chinese Smart Agriculture Policy Texts Based on LDA Model

  • 摘要: 在农业现代化背景下,加快推进智慧农业发展作为关键任务,对抢占农业强国制高点具有重要意义。本文基于2010—2024年74份中央及地方智慧农业综合政策文本,运用LDA主题模型和社会网络分析法系统梳理中国智慧农业政策演进脉络,识别政策核心主题与内在规律,揭示当前政策热点、发展趋势及存在的不足。研究发现,智慧农业政策演进呈现“中央引领、地方跟进”的特征,近年来逐步形成层次清晰、系统性强的政策框架,并在促进产业融合升级、提升农业生产效率和助力乡村振兴等方面成效显著,未来发展空间巨大。然而,其发展面临的技术瓶颈、人才短缺、数据治理等多维度挑战。为此,需从强化央地协同机制、构建多元化人才培养体系、深化智慧农业与数字乡村治理互嵌互融、加强核心技术攻关与转化应用四个方面进行政策动态优化,为智慧农业高质量发展提供有效支撑。

     

    Abstract: In the context of agricultural modernization, accelerating the development of smart agriculture as a key task holds significant importance for securing a leading position in the global agricultural landscape. This paper adopted a policy text analysis perspective to systematically trace the evolution of China’ s smart agriculture policies, identify core themes and underlying patterns, reveal current policy hotspots, trends, and existing shortcomings, and subsequently propose policy recommendations to improve the relevant policy framework. The study found that, policy evolution exhibited a “central government-led, local government-followed” characteristic, with smart agriculture policies covering a broad range of themes, forming a clear-layered, systematic policy framework. In recent years, smart agriculture had achieved significant results in promoting industrial integration and upgrading, improving agricultural production efficiency, and supporting rural revitalization, with vast development potential. However, its development faced multi-dimensional challenges such as technological bottlenecks, talent shortages, and data governance, necessitating the dynamic optimization and precise adaptation of the policy system to provide effective support for the high-quality development of smart agriculture. To this end, policy optimization recommendations are proposed from four aspects: strengthening central-local coordination mechanisms, establishing a diversified talent cultivation system, deepening the integration of smart agriculture and digital rural governance, and intensifying core technology research and application. These recommendations aim to provide theoretical foundations and practical pathways for improving China’ s smart agriculture policy framework.

     

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