Cao Lingjing Zhang Zhiqiang
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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.