Keyword Trends in Artificial Intelligence Research : Analysis of Domestic Academic Papers across Disciplines(2020-2024)

This study analyzes the keywords in artificial intelligence(AI) research papers published in domestic academic journals from 2020 to 2024, identifying their characteristics, annual trends, and disciplinary variations. First, the keywords were examined in terms of notation and quantity. They were mostly in Korean, but there were variations such as English or a combination of Korean and foreign languages. On average, approximately five keywords were listed per paper, ranging from one to twenty-four. Next, an analysis of keyword trends by year showed that the terms representing “artificial intelligence” consistently appeared frequently as keywords. From 2020 to 2021, “deep learning” and “learning”were common, while in 2023-2024, “generative” and “GPT” were frequent keywords. In the social sciences, keywords such as “4차”(industrial phase) and “algorithm” were common. In engineering and natural sciences, “learning,” “deep learning,” and “deep” were frequently used. In interdisciplinary studies, keywords such as “generative,” “chat,” and “챗”(chat) appeared most often. In the humanities, “ChatGPT,” “ethics,” and “literacy”were notable in terms of frequency. In arts and physical education, keywords such as “music education,” “generation,” and “content” stood out. In medical sciences, frequent keywords included “machine,” “medical,” and “neural.” In agricultural, marine, and fisheries sciences, keywords such as “autonomous ships” and “neural network” appeared, distinguishing them from other fields. The study highlights the diversity of AI research across disciplines, with evolving keyword trends reflecting the advancements in the field. AIrelated