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- KOREAN
- E-ISSN3058-311X
E-ISSN : 3058-311X
Vol.2 No.1
Abstract
This study examines the role of the National Library of Korea (NLK) as a key institution for managing national knowledge and cultural resources and as a central data hub in the era of artificial intelligence (AI). It begins by reviewing the paradigm shift in knowledge and information systems driven by AI technologies and investigates the responses of leading national libraries worldwide that have adopted data hub functions. The paper then outlines the NLK’s current status in terms of data construction, service provision, and the characteristics of its data resources, including reliability, comprehensiveness, diversity, openness, scalability, and applicability to AI training. Based on this analysis, the study proposes four strategic directions to enhance the NLK’s capacity as a national data hub. This research aims to provide foundational insight for building a national-level AI training data ecosystem and to reposition the NLK as a core infrastructure for AI-driven knowledge innovation.
Abstract
The digital age has ushered in new possibilities for the humanities, particularly with the emergence of digital humanities, which integrates computer technology. The precursor to digital humanities was "humanities computing," originating with Father Roberto Busa's indexing of medieval Latin. Early digital humanities, alongside computational linguistics and computer science, were applied to statistical data processing in linguistics and archaeology. However, limited computer capabilities restricted its use to text indexing and secondary processing. The 1980s witnessed advancements in computer performance and computational linguistics, enabling large-scale data-driven research in digital humanities. This led to the development of digital resource construction and management, text analysis, and data visualization methods. The advent of big data and generative AI in the 2000s further propelled digital humanities, establishing it as an independent academic field. Linguistics, a hybrid discipline with both humanistic and natural scientific characteristics, finds an optimized application in computational linguistics within the digital humanities. The introduction of digital technology has expanded linguistic methodologies and research subjects to include corpus-based research, computational experimental linguistics, and digital record preservation and analysis. Computational linguistics plays a crucial role in enabling humanities researchers to efficiently explore vast linguistic data and derive meaningful insights through text analysis, semantic analysis, and information extraction. The convergence of digital humanities and computational linguistics is generating new research outcomes across diverse humanities fields such as literature, history, philosophy, and archaeology. Future research should deepen this integrated approach, consider the ethical implications of digital data utilization, and address the social responsibilities arising from the advancement of language technology in the digital age. Through continuous research and innovation, linguistics and computational linguistics are expected to significantly influence the field of digital humanities.
Abstract
This study conducts sentiment analysis on the Korean-translated text of Shakespeare’s Hamlet using two approaches: a lexicon-based method and a Recurrent Neural Network (RNN)-based method. By comparing the analytical outcomes of both approaches, the study evaluates their respective effectiveness in handling texts of varying linguistic complexity. Specifically, it investigates which types of lexical, syntactic or grammatical patterns lead to greater classification errors or reveal strengths in either model. And the research aims to uncover systematic tendencies where semantic-focused (lexicon-based) and syntax-aware (RNN-based) approaches diverge, thereby offering insights into the mechanisms of natural language comprehension in computational systems. Finally, by suggesting literary text as a crucial for evaluating and refining NLP methodologies, this work helps to comprehend the gap between intuitive human language interpretation and machine-based language processing.
Abstract
This study examines the reception of author Pak Kyongni and her novel Land (Toji) as a form of mass literary engagement and introduces a case of building a research-ready dataset from newspaper articles that significantly influenced this reception. The researcher collected and processed articles related to Pak Kyongni and Land, published across 24 newspapers from August 1955 to August 2024, by developing data collection scripts with the help of an AI chatbot. This case demonstrates how humanities researchers can reduce the perceived distance from digital tools and narrow the gap between traditional literary studies and digital humanities through AI-assisted methodologies. In particular, by applying digital approaches to the relatively underexplored field of "mass audience reception history" within Korean literary studies, this research suggests the potential for new methodological developments. It also highlights the academic significance of connecting qualitative and quantitative methods in literary research.
