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Computational analysis of a collaboration network on human-computer interaction in Korea
Seungpeel Lee1,2, Jisu Kim3, Eun Been Choi4
1Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul 03063, Korea.
Mathematical Biosciences and Engineering : MBE
|January 19, 2023
Summary
Collaboration network analysis (CNA) identified key researchers in South Korea's human-computer interaction field. This method revealed influential scientists more effectively than simply tracking publication productivity.
Area of Science:
- Information and Communication Technology (ICT)
- Human-Computer Interaction (HCI)
Background:
- ICT is crucial for developing countries' economic growth.
- International collaboration in ICT research is increasing.
- Human-Computer Interaction is a significant research area within ICT.
Purpose of the Study:
- To analyze research trends and collaboration networks in Korean HCI from 2010-2019.
- To identify key researchers using network analysis metrics.
- To compare the effectiveness of network analysis versus productivity metrics for identifying influential researchers.
Main Methods:
- Collected publication data from SciVal (7,155 publications, 243 authors).
- Performed Collaboration Network Analysis (CNA).
- Utilized centrality metrics (degree, closeness, betweenness) and PageRank to determine network structure and identify key researchers.
Main Results:
- CNA successfully identified key researchers in the field.
- Network analysis revealed influential researchers not apparent from publication counts alone.
- The study provides insights into the structure of HCI research collaboration in Korea.
Conclusions:
- Collaboration Network Analysis is a valuable tool for identifying key opinion leaders in ICT research.
- Network centrality metrics offer a more nuanced understanding of research influence than productivity alone.
- The findings have implications for understanding and fostering research collaborations in emerging technological fields.
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