图书情报学科热点挖掘--基于网络嵌入的大规模关键词共词分析

进行学术期刊关键词分析对于掌握学科主题和学科构成脉络具有重要意义,由此本研究利用网络嵌入技术提取了大型关键词关联网络的高阶信息,并利用聚类算法对“图书馆学;情报学”学科进行关键词主题可视化分析。首先,刻画了关键词之间的局部聚集和全局分布,并分析了最近四年中该学科的热度持续、热度增加和热度减退主题,最后通过国内外关键词关联网络对比揭示了中外研究热点异同。

Hot Topics Detection of Discipline of Library and Information:by Analyzing a Large Scale of Co-Keywords Based on Network Embedding

Keyword analysis of academic journals is of great significance for mastering the subject theme and discipline structure.Therefore,this study uses network embedding technology to extract high-order information of large-scale keyword association network,and uses clustering algorithm to carry out keyword theme visualization analysis of "library science;information science".Firstly,it describes the local aggregation and global distribution of keywords,and analyzes the topics of popularity persistence,popularity increase and popularity decrease in the past four years.Finally,it reveals the similarities and differences between domestic and foreign research hot spots through the comparison of keyword association networks at home and abroad.