IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i24p10855-d1541580.html
   My bibliography  Save this article

Machine Learning-Driven Topic Modeling and Network Analysis to Uncover Shared Knowledge Networks for Sustainable Korea–Japan Intangible Cultural Heritage Cooperation

Author

Listed:
  • Yong-Jae Lee

    (Department of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Republic of Korea)

  • Sung-Eun Park

    (Division of Future Convergence (HCI Science Major), Dongduk Women’s University, Seoul 02748, Republic of Korea)

  • Seong-Yeob Lee

    (Graduate School of Management of Technology, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea)

Abstract

In this study, we provide a comparative analysis of intangible cultural heritage (ICH) research trends in Korea and Japan, aiming to uncover shared knowledge networks and potential areas for sustainable cooperation. We employ a mixed-method approach, combining machine learning-driven topic modeling using Latent Dirichlet Allocation (LDA) and network analysis techniques, to examine a corpus of Korean and Japanese research papers on ICH. LDA topic modeling identified three primary themes: technology and ICH, safeguarding ICH, and methodologies and approaches in ICH research. Comparative analysis reveals distinct characteristics in each country’s approach. Korean research emphasizes practical applications of technology and policy-driven safeguarding strategies, while Japanese research leans towards theoretical exploration and cross-cultural comparisons. Citation network analysis further identifies influential papers and shared knowledge bases, underlining potential opportunities for collaboration. Key findings highlight the potential of technology for ICH preservation and promotion, the necessity of comprehensive safeguarding strategies, and the crucial role of community engagement. Our study suggests that by leveraging their complementary strengths and engaging in collaborative research, Korea and Japan can contribute to the sustainable safeguarding of ICH and foster a deeper understanding of their shared cultural heritage.

Suggested Citation

  • Yong-Jae Lee & Sung-Eun Park & Seong-Yeob Lee, 2024. "Machine Learning-Driven Topic Modeling and Network Analysis to Uncover Shared Knowledge Networks for Sustainable Korea–Japan Intangible Cultural Heritage Cooperation," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:10855-:d:1541580
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/24/10855/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/24/10855/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seulah Kim & Dong-uk Im & Jongoh Lee & Heejae Choi, 2019. "Utility of Digital Technologies for the Sustainability of Intangible Cultural Heritage (ICH) in Korea," Sustainability, MDPI, vol. 11(21), pages 1-19, November.
    2. Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    3. Liangchao Huang & Zhengmeng Hou & Yanli Fang & Jianhua Liu & Tianle Shi, 2023. "Evolution of CCUS Technologies Using LDA Topic Model and Derwent Patent Data," Energies, MDPI, vol. 16(6), pages 1-14, March.
    4. Seok Jin Youn & Yong-Jae Lee & Ha-Eun Han & Chang-Woo Lee & Donggyun Sohn & Chulung Lee, 2024. "A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems," Sustainability, MDPI, vol. 16(15), pages 1-32, August.
    5. Choi, Hyunhong & Woo, JongRoul, 2022. "Investigating emerging hydrogen technology topics and comparing national level technological focus: Patent analysis using a structural topic model," Applied Energy, Elsevier, vol. 313(C).
    6. Sunwoo Park & Namho Chung & Won Seok Lee, 2020. "Preserving the Culture of Jeju Haenyeo (Women Divers) as a Sustainable Tourism Resource," Sustainability, MDPI, vol. 12(24), pages 1-11, December.
    7. Sixuan Liu & Younghwan Pan, 2023. "Exploring Trends in Intangible Cultural Heritage Design: A Bibliometric and Content Analysis," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    8. Song, Kisik & Kim, Karp Soo & Lee, Sungjoo, 2017. "Discovering new technology opportunities based on patents: Text-mining and F-term analysis," Technovation, Elsevier, vol. 60, pages 1-14.
    9. Yong-Jae Lee & Young Jae Han & Sang-Soo Kim & Chulung Lee, 2022. "Patent Data Analytics for Technology Forecasting of the Railway Main Transformer," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Seok Jin Youn & Yong-Jae Lee & Ha-Eun Han & Chang-Woo Lee & Donggyun Sohn & Chulung Lee, 2024. "A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems," Sustainability, MDPI, vol. 16(15), pages 1-32, August.
    2. Yunlei Lin & Yuan Zhou, 2023. "Identification of Hydrogen-Energy-Related Emerging Technologies Based on Text Mining," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
    3. Yong-Jae Lee & Young Jae Han & Sang-Soo Kim & Chulung Lee, 2022. "Patent Data Analytics for Technology Forecasting of the Railway Main Transformer," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    4. Jiwon Yu & Young Jae Han & Hyewon Yang & Sugil Lee & Gildong Kim & Chulung Lee, 2022. "Promising Technology Analysis and Patent Roadmap Development in the Hydrogen Supply Chain," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Dawei Feng & Wenchao Xu & Xinyu Gao & Yun Yang & Shirui Feng & Xiaohu Yang & Hailong Li, 2023. "Carbon Emission Prediction and the Reduction Pathway in Industrial Parks: A Scenario Analysis Based on the Integration of the LEAP Model with LMDI Decomposition," Energies, MDPI, vol. 16(21), pages 1-15, October.
    6. Jinzhu Zhang & Wenqian Yu, 2020. "Early detection of technology opportunity based on analogy design and phrase semantic representation," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 551-576, October.
    7. Yun, Siyeong & Song, Kisik & Kim, Chulhyun & Lee, Sungjoo, 2021. "From stones to jewellery: Investigating technology opportunities from expired patents," Technovation, Elsevier, vol. 103(C).
    8. Sungyong Choi, 2023. "Special Issue on Advances in Operations and Supply Chain Management with Sustainability Considerations," Sustainability, MDPI, vol. 15(6), pages 1-4, March.
    9. Ren, Haiying & Zhao, Yuhui, 2021. "Technology opportunity discovery based on constructing, evaluating, and searching knowledge networks," Technovation, Elsevier, vol. 101(C).
    10. Wu, Yingwen & Ji, Yangjian, 2023. "Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining," Journal of Informetrics, Elsevier, vol. 17(2).
    11. Moon, Seungyeon & Lee, Heesang, 2024. "Identifying technological opportunities using enhanced tech mining: The case of the E-health industry," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    12. Changsok Yoo & Yelim Kim & Jee Hoon Sohn, 2021. "Evaluating the Social Cost of Conflict between New Media and Society: The Case of Gaming Disorder in South Korea," Sustainability, MDPI, vol. 13(14), pages 1-13, July.
    13. Cheng Cao & Haonan Zhu & Zhengmeng Hou, 2024. "Advances in Carbon Capture, Utilization and Storage (CCUS)," Energies, MDPI, vol. 17(19), pages 1-3, September.
    14. Sangmin Lee & Donghan Kim & Sunwoo Park & Wonseok Lee, 2021. "A Study on the Strategic Decision Making Used in the Revitalization of Fishing Village Tourism: Using A’WOT Analysis," Sustainability, MDPI, vol. 13(13), pages 1-12, July.
    15. Zhou, Xiao & Huang, Lu & Porter, Alan & Vicente-Gomila, Jose M., 2019. "Tracing the system transformations and innovation pathways of an emerging technology: Solid lipid nanoparticles," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 785-794.
    16. Alper Bozkurt & Ferhat Şeker, 2023. "Harmonizing Heritage and Artificial Neural Networks: The Role of Sustainable Tourism in UNESCO World Heritage Sites," Sustainability, MDPI, vol. 15(17), pages 1-17, August.
    17. Im, Junyoung & Gye, Hye-Ri & Wilailak, Supaporn & Yoon, Ha-Jun & Kim, Yongsoo & Kim, Hyungchan & Lee, Chul-Jin, 2024. "Hydrogen liquefaction process using carbon dioxide as a pre-coolant for carbon capture and utilization," Energy, Elsevier, vol. 307(C).
    18. Seunghyun Oh & Jaewoong Choi & Namuk Ko & Janghyeok Yoon, 2020. "Predicting product development directions for new product planning using patent classification-based link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1833-1876, December.
    19. Shih-Hao Wang & Chung-Lin Tsai & Han-Chao Chang, 2018. "Laboratory Environmental Conditions Influence Patent Inventors’ Creative Self-efficacy," International Business Research, Canadian Center of Science and Education, vol. 11(5), pages 159-166, May.
    20. Wang, Xuefeng & Zhang, Shuo & Liu, Yuqin & Du, Jian & Huang, Heng, 2021. "How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:10855-:d:1541580. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.