基于智能化公文主题分析的我国政策层级扩散倾向性研究

The Inclination of Vertical Policy Diffusion in China Based on Thematic Analysis

政策创新通过公文流转得以实施和扩散。在大数据背景下,运用政策文本挖掘分析我国不同层级政府间的政策扩散过程,对于了解政策实施效果,推进数字政府建设和提升政府治理能力具有重要意义。然而,当前面向我国政府公文智能处理和政策层级扩散的研究尚未广泛展开。因此,本文通过分析公文文本的结构和内容特征属性,从政策扩散主题维度和政策扩散倾向性两个方面展开研究,尝试分析政策发布时间、布局数量、政策主题强度、执行部门数量等多个维度,构建了一种基于多特征融合的政策扩散倾向性探测模型。同时,本文设计了一种新的针对我国政策层级扩散的可视化图谱,以清晰表达政策在中央、省级以及地市级的主题扩散与变迁。最后,本文以我国大数据政策为例进行了实验,通过大规模政府公文的智能处理与层级扩散倾向性探测,为政策制定者和执行者提供情报支撑和决策参考服务。

Policy innovation is implemented and diffused via document circulation.In the era of big data,it is of great significance to employ document mining to analyze the process of policy diffusion among different levels of government.This will allow a better understanding of policy effects,promote construction of digital government systems,and improve government capabilities.However,at present,little research focus is placed on intelligent processing of government documents and policy diffusion among governments at different levels.In light of this,by this study examines themes in policy diffusion and the inclination of different government levels for policy diffusion by analyzing the structure and content of documents texts,with focus on the time of policy release,the number of policy layouts,the intensity of policy themes,the number of implementing departments,and other characteristics.Based on this analysis,the study proposes an index model to detect policy diffusion inclinations based on multi-feature fusion.Taking the policy of big data as an example,the study designs a visualization map for policy diffusion to express the thematic changes that occur during diffusion of policy from the central government to provincial and municipal levels.Through intelligent processing and theme detection in largescale government document data,this study provides policy makers and implementers with information support and references for decision-making.