政策文本分析文献综述

A Literature Review of Policy Text Analysis

摘要: 数字化时代，政策文本作为社会价值观与政策意图的核心载体，其分析对解构政策本质、支撑公共治理具有关键意义。但现有研究多聚焦单一模块，缺乏“数据源–方法–应用”全链条系统性梳理。本文系统梳理领域研究进展以构建整合分析框架：首先，明确数据源涵盖国家及地方官方文件、专业数据库及政策舆情文本等多元类型；其次，解析文本预处理、内容分析法等基础技术，纳入BERT、LDA、监督式机器学习等前沿方法应用场景；聚焦政策主题演变、协同与冲突剖析、量化评估及多领域实践应用。研究构建技术赋能下的政策文本分析整合框架，揭示机器学习技术对提升分析效率、深度及精准度的核心价值，同时反思政策分析方法应用的挑战，为未来数据质量优化、跨学科融合等方向提出参考。

Abstract: In the digital era, policy texts serve as the core vehicle for social values and policy intentions. Analyzing them is crucial for deconstructing policy essence and supporting public governance. However, existing research often focuses on single modules, lacking systematic integration across the “data source-method-application” chain. This paper systematically reviews field research progress to establish an integrated analytical framework: First, it clarifies data sources encompassing diverse types such as national/local official documents, professional databases, and policy-related public opinion texts. Second, it analyzes foundational techniques like text preprocessing and content analysis, while incorporating cutting-edge methods including BERT, LDA, and supervised machine learning. The study focuses on policy theme evolution, conflict analysis, quantitative evaluation, and multi-domain practical applications. By developing a technology-empowered policy text analysis framework, it reveals the core value of machine learning in enhancing analytical efficiency, depth, and precision. The research also reflects on challenges in policy analysis methodologies, providing references for future improvements in data quality optimization and interdisciplinary integration.