Earticle

초록

영어

The trustworthiness of large language models (LLMs) is becoming increasingly important, but extant review studies have shown two major limitations in dynamically elucidating it over time. First, as of 2024, they have not elucidated the most recent studies on the trustworthiness of LLMs. Second, they have focused on the trustworthiness of LLMs over a limited timespan without considering how it changes over time. To overcome these limitations, this research carried out a state-of-the-art bibliometric analysis on 117 articles on the trustworthiness of LLMs based on two stages of change from a dynamic perspective. Our study revealed the following four findings. First, article publications and citations grew drastically in the first half of 2024, and the trustworthiness of LLMs was confirmed as a recent promising research area in artificial intelligence (AI). Second, business, medicine, and education were especially noteworthy research areas related to the trustworthiness of LLMs. Third, LLM governance was an important recent emergent topic. Fourth, multinational collaboration for the trustworthiness of LLMs was strengthened. We suggest the following topics for future studies on the trustworthiness of LLMs: further promoting LLM governance, employing multidisciplinary and interdisciplinary approaches, and strengthening multinational collaboration.

목차

Abstract
1. Introduction
2. Materials and methods
2.1 Data Retrieval
2.2 Data Analysis Methods
3. Results
3.1 Salient Features of Article Publication and Citation Trends
3.2 Noticeable Features of Research Area Trends
3.3 Salient Features of Thematic Trends
3.4 Noticeable Features of Country Research Collaboration Trends
4. Discussion
4.1 Discussion of Implications of Major Findings
4.2 Suggestions for Research
Acknowledgement
References

키워드

저자

• Yong Sauk Hau [ Professor, Department of Business Administration, Yeungnam University, Korea ]
• Eunmi Kim [ Research Professor, Institute of Management Research, Pusan National University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380