Topic analysis of the research domain in knowledge organization: A latent dirichlet allocation approach

Soohyung Joo, Inkyung Choi, Namjoo Choi

Research output: Contribution to journalArticle

Abstract

Based on text mining, this study explored topics in the research domain of knowledge organization. A text corpus consisting of tides and abstracts was generated from 282 articles of the Knowledge Organisation journal for the recent ten years from 2006 to 2015. Term frequency analysis and Latent Dirichlet allocation topic modeling were employed to analyze the collected corpus. Topic modeling uncovered twenty research topics prevailing in the knowledge organization field, including theories and epistemology, classification scheme, domain analysis and ontology, digital archiving, document indexing and retrieval, taxonomy and thesaurus system, metadata and controlled vocabulary, ethical issues, and others. In addition, topic trends over the ten years were examined to identify topics that attracted more discussion in the journal. The top two topics that received increased attention recently were "ethical issues in knowledge organization" and "domain analysis and ontologies." This study yields insight into a better understanding of the research domain of knowledge organization. Moreover, text mining approaches introduced in this study have methodological implications for domain analysis in knowledge organization.

Original languageEnglish (US)
Pages (from-to)170-183
Number of pages14
JournalKnowledge Organization
Volume45
Issue number2
DOIs
StatePublished - Jan 1 2018
Externally publishedYes

Keywords

  • Domain analysis
  • Knowledge organization
  • KO
  • Research
  • Research trends
  • Topic modeling

ASJC Scopus subject areas

  • Library and Information Sciences

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