引文内容视角下的引文网络知识流动效应研究

Network Analysis on Knowledge Flow in Citation Network from the Perspective of Citation Content

【目的/意义】利用网络分析方法对融入引文内容的引文网络中的知识流动规律与模式展开系统研究,以期为引文网络中的知识扩散、转化与创新提供理论与实证依据。【方法/过程】选取描述性统计量和网络分析指标,对知识节点的知识流动能力及角色、知识群落的知识流动类型及结构、整体网络的知识流动分布特征及结构特征进行深度刻画和剖析。【结果/结论】依据CNKI数据库主题期刊论文为测度数据,分别构建"智库""数字人文""数据治理"三个主题的引文网络,并依据文中方法比较分析其间知识流动特征的异同。文中方法能够深入挖掘学术文献间的知识关联,弥补过去引文网络知识流动研究中因忽略深层次引用信息而产生的缺陷。【创新/局限】本文采用多种指标与方法对引文内容视角下引文网络知识流动规律与模式展开系统研究,但是未从整体引文网络中抽取反映某一或某些知识属性的个体引文网络进行分析。

【Purpose/significance】The research makes a systematic study of the knowledge flow pattern in the citation network with the method of network analysis, so as to provide theoretical and empirical basis for the knowledge diffusion, transformation and innovation in the citation network.【Method/process】Descriptive statistics and network analysis indexes is selected to describe and analyze the ability and role of knowledge flow of knowledge nodes, the type and structure of knowledge flow of knowledge community, the distribution and structure characteristics of knowledge flow of the whole network.【Result/conclusion】 According to CNKI database, citation networks of "Think Tank", "Digital Humanities" and "Data Governance" is constructed respectively, and the similarities and differences of knowledge flow characteristics between them is compared and analyzed according to the methods in this paper. The method in this paper can deeply mine the knowledge association among academic documents, and make up for the defects of neglecting the deep-seated reference information in the past research.【Innovation/limitation】This article uses a variety of indicators and methods to systematically study the laws and patterns of citation network knowledge flow from the perspective of citation content, but does not extract individual citation networks that reflect one or some knowledge attributes from the overall citation network for analysis.