LDA 토픽 모델링을 활용한 디지털 무역 연구동향 분석

초록

The purpose of this study is to help determine future research direction by analyzing trends and key topics in the field of digital trade. For this purpose, 136 papers published from 1990 to 2024 in domestic academic papers related to the digital trade through the Research Information Sharing Service(RISS) were selected and conducted TF-IDF, Latent Dirichlet Allocation(LDA) analysis using the TextTom program. Some of the results are summarized as follows: As a results of TF-IDF analysis, words such as 'electronic', 'trade', 'e-commerce', 'agreement', 'export' and 'bill of lading’ were derived as key words. In the LDA topic modeling, a total of six topics were derived, and they were named 'Digital Trade Rules', 'Digital Technology and Blockchain', 'Digitalization of Trade Documents and Electronic Bills of Lading', 'Digital Trade Policy', 'Digital Trade and Data', 'Digital Trade and Payment', respectively. There was a high content similarity between the key words of TF-IDF analysis and the topic of LDA analysis. In the field of digital trade, it was confirmed that research is being conducted in both institutional and technological aspects.

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