Data-Driven Approach to Identify Research Topics for Science and Technology Diplomacy

• Published in: 한국콘텐츠학회 논문지, 20(11) Vol. 20; no. 11; pp. 216 - 227
• Main Authors: Woon-Dong Yeo(여운동), Seonho Kim(김선호), BangRae Lee(이방래), Kyung-Ran Noh(노경란)
• Format: Journal Article
• Language: English
• Published: 한국콘텐츠학회 01.11.2020
• Subjects: 학제간연구; Scientometrics; 추천시스템; Deep Learnining; 과학계량학; Bibliometrics; 딥러닝; Science for Diplomacy; Recommender System; 계량서지학; 과학외교
• ISSN: 1598-4877; 2508-6723
• DOI: 10.5392/JKCA.2020.20.11.216

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. KCI Citation Count: 0