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Use of Triangulation in Comparing the Blockchain Knowledge Structure between China and South Korea: Scientometric Network, Topic Modeling, and Prediction Technique

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  • Yu-Peng Zhu

    (Blockchian Policy Research Center, Cyber Emotions Research Institute, Yeungnam University, Gyeongsan-si 38541, Korea
    Department of Media and Communication, Yeungnam University, Gyeongsan-si 38541, Korea)

  • Han-Woo Park

    (Department of Media and Communication, Yeungnam University, Gyeongsan-si 38541, Korea
    Interdisciplinary Graduate Programs of Digital Convergence Business, Yeungnam University, Gyeongsan-si 38541, Korea
    Interdisciplinary Graduate Programs of East Asian Cultural Studies, Yeungnam University, Gyeongsan-si 38541, Korea)

Abstract

Blockchain, as a new innovative technology, has become a popular topic in many fields in recent years. In this study, triangulation was used to investigate the development of knowledge structures. First, scientometric network analysis was employed to identify the cooperation of knowledge networks. It was found that the structure of blockchain knowledge networks in China is relatively more complex and diverse than in South Korea. Since increased teamwork in blockchain is conducive to the creation of high-quality knowledge products, the Chinese government appears to strongly promote diversified cooperation on blockchain technology through centralized policies. Second, machine-learning topic modeling was used to analyze the content exchanged via a collaborative network. As a result, it was found that both countries lacked the societal and commercial aspects of blockchain technology. Finally, we developed a prediction technique based on the Ernie model to automatically categorize the nature of blockchain research.

Suggested Citation

  • Yu-Peng Zhu & Han-Woo Park, 2022. "Use of Triangulation in Comparing the Blockchain Knowledge Structure between China and South Korea: Scientometric Network, Topic Modeling, and Prediction Technique," Sustainability, MDPI, vol. 14(4), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2326-:d:752374
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    References listed on IDEAS

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