Kim, Donghun

<SCI & SSCI>

• Kim, D., Quan, L., Seo, M., Kim, K., Kim, J.W., & Zhu, Y. (2023). Interpretable machine learning-based approaches for understanding suicide risk and protective factors among South Korean females using survey and social media data. Suicide and Life-Threatening Behavior
• Kim, D., Jung, W., Jiang, T., & Zhu, Y. (2023). An Exploratory Study of Medical Journal’s Twitter Use: Metadata, Networks, and Content Analyses. Journal of Medical Internet Research, 25, e43521.
• Nam, S., Kim, D., Jung, W., & Zhu, Y.(2022). Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis. Journal of Medical Internet Research, 24(4):e28114
• Kim, D., Jung, W., Nam, S., Jeon, H., Baek, J., & Zhu, Y. (2022). Understanding information behavior of South Korean Twitter users who express suicidality on Twitter. Digital health, 8.
• Yi, Y. J., Hwang, B., & Kim, D. (2022). A model for mobile curation services in academic libraries. The Electronic Library.
• Jung, W., Kim, D., Nam, S., & Zhu, Y.(2021). Suicidality detection on social media using metadata and text feature extraction and machine learning. Archives of Suicide Research.
• Zhu, Y., Kim, D., Yan, E., Kim, M. C., & Qi, G. (2020). Analyzing China’s research collaboration with the United States in high-impact and high-technology research. Quantitative Science Studies, 1-17.

<KCI>

• Kim, D., Jiang, T., & Zhu, Y. (2021). Exploring Opinions on University Online Classes During the COVID-19 Pandemic Through Twitter Opinion Mining, Journal of the Korean Society for Library and Information Science, 55(4), 5–22.
• Kim, D., Oh, C., & Zhu, Y. (2021). Analyzing Research Trends in Blockchain Studies in South Korea Using Dynamic Topic Modeling and Network Analysis, Journal of the Korean Society for Information Management (JKOSIM), 38(3), 23–39.
• Kim, D., Kim, K., & Zhu, Y. (2021). A Bibliometric Analysis of the Major Korean Journals Indexed in 2020 Google Scholar Metrics, Journal of the Korean Society for Information Management (JKOSIM), 38(1), 53–69.
• Kim, D., & Yi. Y. (2020). The Effect of Innovation Resistance of Users on Intention to Use Mobile Health Applications. Journal of the Korean BIBLIA Society for library and Information Science, 31(1), 5–20. https://doi.org/10.14699/KBIBLIA.2020.31.1.005
• Zhu, Y., Kim, D., Lee, C., &Yi. Y. (2019). Investigating Major Topics through the Analysis of Depression-related Facebook Group Posts. Journal of the Korean Society for Library and Information Science, 53(4), 171-187.

<Dissertation>

  Kim, D (2020). The Effect of Innovation Resistance of Users on Intention to Use Mobile Health Applications(Masters Dissertation). SungKyunKwan University, Seoul, Korea.

• 2021 SKKU Research Matters, 총장상. 성균관대학교
• 2021 KOPIS 빅데이터 분석 공모전, 우수상 [지도]. 문화체육관광부
• 2021 SKKU 대학원생 논문공모, 최우수상. 성균관대학교
• 2020 SKKU 성공스토리 공모전, 우수상. 성균관대학교 학생성공센터
• 27th Conference on Korean Society for Information Society, BEST POSTER AWARD. Korean Society for Information Society
• 2019 국립암센터 빅데이터공모전, 대상. 국립암센터
•  2019 International Conference on Health Data and Information Services, BEST POSTER AWARD. SungKyunKwan University
The 13th Library Innovation Idea Papers and Best Practices, Participation Prize. National Library of Korea 

Email: dhkim91@yonsei.ac.kr