Topic analysis and development in knowledge graph research: A bibliometric review on three decades

Xieling CHEN, Haoran XIE, Zongxi LI, Kwok Shing CHENG

Research output: Contribution to journalArticlespeer-review

1 Citation (Scopus)

Abstract

Knowledge graph as a research topic is increasingly popular to represent structural relations between entities. Recent years have witnessed the release of various open-source and enterprise-supported knowledge graphs with dramatic growth in applying knowledge representation and reasoning into different areas like natural language processing and computer vision. This study aims to comprehensively explore the status and trends – particularly the thematic research structure – of knowledge graphs. Specifically, based on 386 research articles published from 1991 to 2020, we conducted analyses in terms of the (1) visualization of the trends of annual article and citation counts, (2) recognition of major institutions, countries/regions, and publication sources, (3) visualization of scientific collaborations of major institutions and countries/regions, and (4) detection of major research themes and their developmental tendencies. Interest in knowledge graph research has clearly increased from 1991 to 2020 and is continually expanding. China is the most prolific country in knowledge graph research. Moreover, countries/regions and institutions that have higher levels of international collaboration are more impactful. Several widely studied issues such as knowledge graph embedding, search and query based on knowledge graphs, and knowledge graphs for intangible cultural heritage are highlighted. Based on the results, we further summarize perspective directions and suggestions for researchers, practitioners, and project managers to facilitate future research on knowledge graphs. Copyright © 2021 Elsevier B.V. All rights reserved.
Original languageEnglish
JournalNeurocomputing
Early online dateJun 2021
DOIs
Publication statusE-pub ahead of print - Jun 2021

Citation

Chen, X., Xie, H., Li, Z., & Cheng, G. (2021). Topic analysis and development in knowledge graph research: A bibliometric review on three decades. Neurocomputing. Advance online publication. doi: 10.1016/j.neucom.2021.02.098

Keywords

  • Knowledge graphs
  • Bibliometric analysis
  • Structural topic modeling
  • Research topics
  • Scientific collaboration
  • PG student publication

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