• Title/Summary/Keyword: Deep Learnining

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Data-Driven Approach to Identify Research Topics for Science and Technology Diplomacy (과학외교를 위한 데이터기반의 연구주제선정 방법)

  • Yeo, Woon-Dong;Kim, Seonho;Lee, BangRae;Noh, Kyung-Ran
    • The Journal of the Korea Contents Association
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    • v.20 no.11
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    • pp.216-227
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    • 2020
  • In science and technology diplomacy, major countries actively utilize their capabilities in science and technology for public diplomacy, especially for promoting diplomatic relations with politically sensitive regions and countries. Recently, with an increase in the influence of science and technology on national development, interest in science and technology diplomacy has increased. So far, science and technology diplomacy has relied on experts to find research topics that are of common interest to both the countries. However, this method has various problems such as the bias arising from the subjective judgment of experts, the attribution of the halo effect to famous researchers, and the use of different criteria for different experts. This paper presents an objective data-based approach to identify and recommend research topics to support science and technology diplomacy without relying on the expert-based approach. The proposed approach is based on big data analysis that uses deep-learning techniques and bibliometric methods. The Scopus database is used to find proper topics for collaborative research between two countries. This approach has been used to support science and technology diplomacy between Korea and Hungary and has raised expectations of policy makers. This paper finally discusses aspects that should be focused on to improve the system in the future.