政策信息学是大数据科学范式下政策科学向大数据政策知识发现研究发展的跨学科研究方向，从该理论视角系统梳理政策文本量化的知识发现方法及最新研究进展，可以指导数据密集的政策文本分析实践。文章基于政策信息学理论分析政策文本量化研究兴起背景、概念内涵和研究框架，将现有研究归纳为面向政策结构特征的政策计量分析、面向政策内容特征的政策内容量化和面向政策语义特征的政策文本挖掘等三类研究方法，分别总结各类量化方法的研究流程、主要类型及优缺点，并系统论述政策文本量化知识发现研究进展。政策文本量化研究近年来发展迅速，集中体现在政策信息爆炸性增长、多领域方法交叉融合现象凸显、政策分析需求复杂多样。未来应重点关注：建设领域政策大数据库、开发针对性的方法工具以及注重理论研究实践落地。

Policy Informatics is an interdisciplinary research direction developed from policy science to big data policy knowledge discovery research under the research paradigm of big data science. From this theoretical perspective, it systematically combs the current situation and latest progress of knowledge discovery research methods in policy text quantitative, which can guide the practice of policy text analysis of data density. This paper analyzes the background, concept connotation and research framework of quantitative research on policy text from the theory of Policy Informatics, and classifies the existing research into three types of research methods: policiometrics analysis based on policy structural features, policy content quantification based on policy content features, and policy text mining based on policy semantic features. It summarizes the research process, main types, advantages and disadvantages of various quantitative methods, and systematically discusses the research progress of knowledge discovery in policy text quantification. Knowledge discovery research on policy text quantification has developed rapidly in recent years, which is mainly reflected in the explosive growth of policy information, the prominent phenomenon of cross integration of multi domain methods, and the complex and diverse demand for policy analysis. In the future, we should focus on: building a large policy database in the field, developing targeted methods and tools, and paying attention to the implementation of theoretical research.