Date of Publication:2017-01-01

Journal:情报学报

Affiliation of Author(s):经济管理学院

Issue:1

Page Number:100-110

ISSN No.:1000-0135

Abstract:The grasping of key research topics in disciplines and academic domains is of great importance for both scientific researchers and policy-makers.A method is proposed in this paper to identify the key research topics and their evolutionary paths through the detection of communities in the "partial-cumulative" citation network.The proposed method is examined in the research field of "evolution of cooperation".By constructing seven successive citation networks in this field,the key topics are identified through community detection and the evolutionary paths of topics are tracked by detecting the strong connections between communities in adjacent time-slices;and the interrelationships between the identified topics can accordingly be analyzed.The proposed method has better performance in the accuracy in topic identification in the "evolution of cooperation" dataset in comparison with the methods based on bibliographic coupling networks and co-citation networks,indicating that the proposed method may complement the existing citation-based methods for topic identification and tracking of topic evolution.

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