Analysis of Research Hotspots and Trends in Generative AI in South Korea: A Visual Metric Analysis Based on CiteSpace and VOSviewer Knowledge Graphs
Ling-Yi Li, Hoe-Kyung Jung, So-Hyun Kim, Han-Kil Kim
The Journal of the Korea Contents Association
Problems Identified (4)
research trend identification: The study aims to identify research trends and concentrated research areas in South Korea's generative AI field.
future development forecasting: The study aims to predict future development trends in South Korea's generative AI research.
research trend identification: The study aims to identify research trends and concentrated research areas in South Korea's generative AI field.
future development forecasting: The study aims to predict future development trends in South Korea's generative AI research.
Proposed Solutions (2)
bibliometric knowledge-map analysis: The paper performs bibliometric analysis of 592 Web of Science papers from 2018 to 2025 using VOSviewer and CiteSpace visualization software to derive knowledge maps.
bibliometric knowledge-map analysis: The paper performs bibliometric analysis of 592 Web of Science papers from 2018 to 2025 using VOSviewer and CiteSpace visualization software to derive knowledge maps.
Results (3)
post-2024 publication surge:
core topics identified:
technology-application direction:
Research Domain
Bibliometric analysis of generative AI research in South Korea