Topic Analysis of the Research Domain in Knowledge Organization: A Latent Dirichlet Allocation Approach

Soohyung Joo; Inkyung Choi; and Namjoo Choi

doi:10.5771/0943-7444-2018-2-170

Contents
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- 93–94 Titelei/Inhaltsverzeichnis 93–94
- 95–96 15th International ISKO Conference 95–96
- 96–96 ISKO 2018 General Assembly Provisional Agenda 96–96
- 97–102 Obituary 97–102
  - In Memoriam: Eric Coates, 1916-2017 Keiichi Kawamura Keiichi Kawamura
- 103–107 Feature 103–107
  - Bibliography of Published Works by Eric James Coates Keiichi Kawamura Keiichi Kawamura
- 108–183 Articles 108–183
  - 108–124 Wikipedia HTML Structure Analysis for Ontology Construction Rim Zarrad, Narjes Doggaz, and Ezzedine Zagrouba Rim Zarrad, Narjes Doggaz, and Ezzedine Zagrouba 108–124
  - 125–136 Knowledge Organization: From Term to Concept, From Concept to Domain Aline Ellis Arboit Aline Ellis Arboit 125–136
  - 137–151 Experience-Oriented Knowledge Organisation for the Transference of Scientific Knowledge from Universities to SMEs Marianne Lykke, Sarai Løkkegaard, and Christian Jantzen Marianne Lykke, Sarai Løkkegaard, and Christian Jantzen 137–151
  - 152–169 Using Knowledge Organization Systems to Automatically Detect Forward-looking Sentiment in Company Reports to Infer Social Phenomena Paul Hugh Cleverley, Laura Joy Muir Paul Hugh Cleverley, Laura Joy Muir 152–169
  - 170–183 Topic Analysis of the Research Domain in Knowledge Organization: A Latent Dirichlet Allocation Approach Soohyung Joo, Inkyung Choi, and Namjoo Choi Soohyung Joo, Inkyung Choi, and Namjoo Choi 170–183
- 184–201 Reviews of Concepts in Knowledge Organization 184–201
  - Mathematical Theory of Classification Daniel Parrochia Daniel Parrochia
- 202–204 Books Recently Published 202–204
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KO KNOWLEDGE ORGANIZATION , page 170 - 183

Topic Analysis of the Research Domain in Knowledge Organization: A Latent Dirichlet Allocation Approach

Autoren

Soohyung Joo Inkyung Choi and Namjoo Choi

DOI
- doi.org/10.5771/0943-7444-2018-2-170
- ISSN: 0943-7444
- ISSN online: 2942-3309
Abstract

Based on text mining, this study explored topics in the research domain of knowledge organization. A text corpus consisting of titles and abstracts was generated from 282 articles of the Knowledge Organization 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.
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