Title
Exploring the topic hierarchy of digital library research in China using keyword networks: a K-core decomposition approach.
Abstract
Exploring the topic hierarchy of a research field can help us better recognize its intellectual structure. This paper proposes a new method to automatically discover the topic hierarchy, in which the keyword network is constructed to represent topics and their relations, and then decomposed hierarchically into shells using the K-core decomposition method. Adjacent shells with similar morphology are merged into layers according to their density and clustering coefficient. In the keyword network of the digital library field in China, we discover four different layers. The basic layer contains 17 tightly-interconnected core concepts which form the knowledge base of the field. The middle layer contains 13 mediator concepts which are directly connected to technology concepts in the basic layer, showing the knowledge evolution of the field. The detail layer contains 65 concrete concepts which can be grouped into 13 clusters, indicating the research specializations of the field. The marginal layer contains peripheral or isolated concepts.
Year
DOI
Venue
2016
10.1007/s11192-016-2051-x
Scientometrics
Keywords
Field
DocType
Intellectual structure,Topic hierarchy,Keyword network,K-core decomposition,Digital library in China
Data mining,Cluster (physics),Computer science,Knowledge evolution,Decomposition method (constraint satisfaction),Intellectual structure,Knowledge base,Digital library,Hierarchy,Clustering coefficient
Journal
Volume
Issue
ISSN
108
3
0138-9130
Citations 
PageRank 
References 
0
0.34
19
Authors
5
Name
Order
Citations
PageRank
Lu Xiao100.34
Guonan Chen200.68
Jianjun Sun3193.07
Shuguang Han416818.43
Chengzhi Zhang56924.42