黄萃,吕立远

• 1:浙江大学公共管理学院
• 2:清华大学公共管理学院

摘要(Abstract)：

数据时代的来临深刻影响了社会科学的研究范式。在不断增长的社会数据中,文本数据扮演着重要的角色,公共管理与公共政策领域开始越来越多地应用文本分析。本文基于"研究语料—研究逻辑"的类型学分析框架对文本分析在公共管理与公共政策研究领域的研究方法应用进行了研究综述。探讨了公共管理与公共政策领域涉及的文本分析研究在不同维度的分布情况,展望本领域发展文本分析方法的潜在路径。本文指出,文本分析将逐渐从分析文本的结构化特征向非结构化特征发展,从开展描述性推论向因果推论发展;为更好地实现上述发展进程,研究者应收集更为高频的文本数据,并尝试将文本数据与更加丰富的数据源相结合。

关键词(KeyWords)： 文本分析;公共管理;公共政策;研究综述

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金优秀青年科学基金项目“公共管理与公共政策”(项目批准号:71722002);国家自然科学基金面上项目“基于府际关系的公共政策工具选择组合与扩散量化研究——以科技金融领域为例”(项目批准号:71673164)资助

作者(Author): 黄萃,吕立远

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• (1)考虑到本领域的交叉学科属性，笔者采用广义的检索策略。对于英文文献，将检索范围扩展到Web of Science核心合集中“Public Administration”“Management”“Political Science”“Social Science Interdisciplinary”和“Social Issues”等可能涉及公共管理的领域。对于中文文献，将检索范围确定为CNKI数据库中的核心期刊和CSSCI期刊，分类目录选定为社会科学Ⅰ辑、Ⅱ辑中的“政治学”“行政学与国家行政管理”“政党与群众组织”“社会科学理论与方法”和“社会学与统计学”等以及经济与管理科学大类。对于文献的时间范围，笔者未进行限制，即呈现数据库中所有包含相关关键词文献的时间分布趋势。
• (2)参见:Grimmer and Stewart(2013),Gentzkow et al.(2017),Berger et al.(2020)。
• (1)该三类特征来源于文本的内容特征，但加工后已成为类似于“主题词”的形式特征概念，因而在形式特征部分予以介绍。
• (1)指数随机图模型是一种静态的网络动力学模型，本质上在回答哪些因素促使节点在一个截面的网络中建立起更多(少)的连接关系。
• (1)由于本章主要讨论文本分析的发展趋势，文献选取主要从分析文本分析模式切入，故部分前沿文献超出了公共管理范畴，但相关分析思路对于发展公共管理与公共政策领域的文本分析具有借鉴意义。
• (1)可参见:https://visuals.manifesto-project.wzb.eu/mpdb-shiny/cmp_dashboard_dataset/。