吕立远,黄萃

• 1:清华大学公共管理学院
• 2:教育部科技委战略研究基地:清华大学科教政策研究中心
• 3:浙江大学公共管理学院

摘要(Abstract)：

多元主体间的复杂关系深刻影响着公共事务的运行。网络分析在厘清社会互动结构中扮演着重要角色,始终是公共管理和公共政策研究的重要方法。然而,现有的网络研究在多元的网络对象上并未取得一致的结论,公共管理和公共政策研究者亟须进一步提升网络研究的分析深度。本文从方法论层面对上述问题进行探讨,指出侧重描述的研究传统、偏向案例的研究设计和未能充分跟进前沿技术进展等是现阶段拓展网络研究深度的主要制约因素。基于“网络复杂度—时序变化”的类型学框架,本文对现有网络分析文献在四个象限的研究谱系进行综述,探讨了本领域网络研究的发展方向,指出未来应进一步关注人机协作、跨层次协作等新兴网络关系类型,并借助实体抽取等技术进展进一步提升网络关系采集的效率和稳健性,发展和集成适用于复杂条件的网络分析工具,更多地尝试探索网络对象的一般规律。此外,经典网络分析方法往往更加侧重于个体的社会嵌入性,通过结合博弈论、多主体仿真等前沿方法,研究者可以实现分析“社会嵌入性”和“主观能动性”的统一,以复杂系统视角进一步加深对于复杂公共治理问题的理解。

关键词(KeyWords)： 网络分析;公共管理;公共政策;解释性研究;研究综述

Abstract:

Keywords:

基金项目(Foundation): “科技创新2030—‘新一代人工智能’”重大项目“人工智能综合影响社会实验研究”(项目批准号:2020AAA0105400);; 国家自然科学基金创新群体项目“中国公共政策理论与治理机制”(项目批准号:71721002);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);国家自然科学基金重点项目“基于社会实验的人工智能社会综合影响与作用机制研究”(项目批准号:72134007)资助;; 清华大学自主科研计划项目(项目批准号:20201080726)

作者(Author): 吕立远,黄萃

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