基于引文网络重叠社团发现的图书情报领域学科主题结构分析

Mapping the Subject Structure of Library and Information Science through Overlapping Community Detection in Citation Network

描绘学科主题结构能促进学科理论和方法研究,助力学科创新发展。本文提出基于重叠社团发现算法可视化学科主题结构,利用有向h度测度学科主题间知识流动,以拓扑结构和内容揭示重叠节点角色,并以图书馆学和情报学为研究对象检验了方法的有效性。结果表明,这一方法能够挖掘出细粒度的研究主题,展现学科主题结构。情报学和图书馆学理论研究、知识管理、引文分析、智慧图书馆、图书馆学科服务等主题与其他研究主题连接紧密。重叠节点分化为具有高介数中心性和度的核心节点,以及低介数中心性和度的边缘节点。情报学和图书馆学学科界限模糊,研究主题呈现同质和分野的特点,在深化学科理论研究的基础上促进学科深度融合将有助于学科发展。

Mapping the subject structure can promote theoretical and methodological research—further accelerating a discipline's innovation and development.This paper proposes to visualize subject structure based on an overlapping community detection algorithm,which measures the knowledge flow between topics through directed h-degree and reveals overlapping node roles through the analysis of topological structure and content.We apply this method to the field of library and information science.The results show that the method can dig out fine-grained research topics.These topics,which include theoretical research in information science and library science,knowledge management,citation analysis,smart library,and library subject service,are closely related to other topics.Overlapping nodes are divided into core nodes,which have a higher betweenness centrality and degree,and edge nodes,which have a lower betweenness centrality and degree.The boundary between information science and library science is fuzzy,and the research subject is homogeneous and differentiated.A deep discipline integration,which must be based on facilitating the theoretical and practical research of the two disciplines,will accelerate the development of library and information science.