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Analysis of Research Topics among Library, Archives and Museums using Topic Modeling

  • Journal of Korean Library and Information Science Society
  • Abbr : JKLISS
  • 2019, 50(4), pp.339-358
  • DOI : 10.16981/kliss.50.4.201912.339
  • Publisher : Korean Library And Information Science Society
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : November 20, 2019
  • Accepted : December 12, 2019
  • Published : December 31, 2019

Heesop Kim 1 Kang Bora 1

1경북대학교

Accredited

ABSTRACT

The purpose of this study is to understand the topics of the research for the establishment of cooperative platform between libraries, archives, and museums that carry out the common task of providing knowledge information in a broad sense. To achieve the purpose of this study, 637 bibliographic information on three institutions were collected from the Web version of Scopus database. Among the collected bibliographic information, 5,218 words were extracted through NetMiner V.4 and analysed topic modeling. The results are as follows: First, as a result of analyzing the frequency of word appearance according to the tf-idf weight ‘Preservation’ was the most hottest topic. Second, the topic modeling analysis through LDA(Latent Dirichlet Allocation) algorithm resulted in 13 topic areas. Third, as a result of expressing 13 topic areas as a network, repository construction was the central topic, and the research topics such as cooperation among institutions, conservation environment for collections, system and policy discovery, life cycle of collections, exhibition of information resources, and information retrieval were closely related to the central topic. Fourth, the trend of 13 topic areas by year 1998 is limited to the specific subjects such as system and policy discovery, information retrieval, and life cycle of collections, while the subsequent studies have been carried out after that year.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.