Knowledge structure transition in library and information science: topic modeling and visualization
Knowledge structure transition in library and information science: topic modeling and visualization
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图书情报学知识结构变迁:主题建模与可视化
DOI:
10.1007/s11192-020-03657-5
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发表时间:
2020
期刊:
影响因子:
3.9
通讯作者:
Kurata Keiko
中科院分区:
文献类型:
--
作者:
Miyata Yosuke;Ishita Emi;Yang Fang;Yamamoto Michimasa;Iwase Azusa;Kurata Keiko
The purpose of this research is to identify topics in library and information science (LIS) using latent Dirichlet allocation (LDA) and to visualize the knowledge structure of the field as consisting of specific topics and its transition from 2000–2002 to 2015–2017. The full text of 1648 research articles from five peer-reviewed representative LIS journals in these two periods was analyzed by using LDA. A total of 30 topics in each period were labeled based on the frequency of terms and the contents of the articles. These topics were plotted on a two-dimensional map usingLDAvisand categorized based on their location and characteristics in the plots. Although research areas in some forms were persistent with which discovered in previous studies, they were crucial to the transition of the knowledge structure in LIS and had the following three features: (1) The Internet became the premise of research in LIS in 2015–2017. (2) Theoretical approach or empirical work can be considered as a factor in the transition of the knowledge structure in some categories. (3) The topic diversity of the five core LIS journals decreased from the 2000–2002 to 2015–2017.