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Comparison of Topic Modeling Methods for Analyzing Research Trends of Archives Management in Korea: focused on LDA and HDP

  • Journal of Korean Library and Information Science Society
  • Abbr : JKLISS
  • 2017, 48(4), pp.235-258
  • DOI : 10.16981/kliss.48.4.201712.235
  • Publisher : Korean Library And Information Science Society
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : November 16, 2017
  • Accepted : December 16, 2017

PARK JUNHYEONG 1 HyoJung Oh 1

1전북대학교

Accredited

ABSTRACT

The purpose of this study is to analyze research trends of archives management in Korea by comparing LDA (Latent Semantic Allocation) topic modeling, which is the most famous method in text mining, and HDP (Hierarchical Dirichlet Process) topic modeling, which is developed LDA topic modeling. Firstly we collected 1,027 articles related to archives management from 1997 to 2016 in two journals related with archives management and four journals related with library and information science in Korea and performed several preprocessing steps. And then we conducted LDA and HDP topic modelings. For a more in-depth comparison analysis, we utilized LDAvis as a topic modeling visualization tool. At the results, LDA topic modeling was influenced by frequently keywords in all topics, whereas, HDP topic modeling showed specific keywords to easily identify the characteristics of each topic.

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.