LDA 토픽모델링을 활용한 인공지능 리터러시에 대한 주요 이슈 분석
An Analysis of Issues on AI Literacy Using LDA Topic Modeling
- 발행
- 2025 등록이 논문은 발행 시점을 확인하지 못해 원문 등록일을 적었습니다. KCI가 2005~2008년에 옛 논문을 몰아서 올린 탓에, 그 시기 등록분은 발행보다 평균 3~5년 늦습니다. 실제 발행연도는 더 이를 수 있습니다.
- 소속·발행
- 조선대학교 경영학부
- 출처
- 국내 KCI
- DOI
- 10.37272/JIECR.2024.12.24.6.71
- 원문
- 원문 보기 ↗
개념
키워드
Artificial Intelligence Literacy, Topic Modeling, Latent Dirichlet Allocation (LDA), Artificial Intelligence Literacy, Topic Modeling, Latent Dirichlet Allocation (LDA)
초록
Artificial Intelligence (AI) literacy is increasingly essential as AI technologies continue to shape modern society. This study examines AI literacy using Latent Dirichlet Allocation (LDA) topic modeling on news articles to identify key themes and public perceptions. The analysis highlights significant issues such as the need for AI education, the role of policy in addressing AI-related challenges, and the societal implications of AI technologies. Findings reveal evolving discourse around AI literacy, from conceptual understanding to practical applications in education, industry, and social equity. This research provides valuable insights for developing effective AI literacy programs and policies, promoting informed decision-making, and addressing disparities in AI understanding. The results contribute to advancing AI literacy as a multidisciplinary field with educational, social, and policy implications.