디지털인문학
- E-ISSN : 3058-311X
- Publisher : 한국디지털인문학협의회
- CCL :
6개 논문이 있습니다.
This essay is a prompt response to Matthew Kirschenbaum and Rita Raley’s essay “AI and the University as a Service” published in the most recent issue of PMLA. I diagnose the anticipated problem of higher education in the era of AI as the “global digitalization of the university and language.” By the digitalization of the university, I mean the online circulation of recorded courses. By the digitalization of language, my approach broadens to refer not only to the proliferation of online resources but also the dissemination of language into machine-readable units and their redistribution. My positionality in interpreting these kinds of digitalization is global, involving multilingual, multicultural contexts. The possibilities and challenges concern the use of LLMs for language education and writing pedagogy in higher education in two aspects: 1) whether it is justifiable to train students using the language of LLM outputs based on statistical probability rather than communicative intent; 2) how to decolonize the English monopoly on language education and data structures. My suggestions are open-ended, reminding us humanists of the Korean resources that are widely accessible and the co-evolutionary approach of writing with AI. All we need in future higher education may be APT (AI Personal Training).
Most network analyses of narrative texts have focused on character interactions, often limiting their scope to social relationships as envisioned by social network analysis. This paper, however, presents a network analysis of the narrator and the main character in F. Scott Fitzgerald's The Great Gatsby, expanding on my previous research that examined characters as networks of words within a dramatic narrative. I conceptualize the narrator and characters as lexical networks derived from the novel's dialogues and narration. A "symptomatic reading" of a character's speech network uncovers hidden aspects of that character, such as Gatsby's obsessive desire for Daisy and fixation on the lost past. Furthermore, analyzing a character's ego network within the narrator's narration reveals how the narrative voice understands and portrays that character. Specifically, Gatsby's ego network exposes the narrator's preoccupation with physical appearances, his subtle male gaze, his speculation about Gatsby's mysterious past, and his narrative strategy to mythologize Gatsby through temporal and spatial movements. Finally, the bipartite network between the narrator and the character, mediated through shared words, illustrates points of convergence and divergence, emphasizing the stark contrast between Gatsby as a character and Nick as the narrator. This study demonstrates how computational literary criticism can contribute to digital humanities by providing a refined examination of literary texts while creatively employing digital methodologies.
This paper analyzes the discourse and meaning of ‘Sovereignty’ in the First Republic of Korea by employing text mining methodology, based on 859 sovereignty-related articles from Kyunghyang Shinmun, Dong-A Ilbo, and Chosun Ilbo published during the era. Topic modeling - the Natural Language Processing(NLP) technology that integrates Machine Learning - was used to uncover the discourse related to the concept of sovereignty at a macro level, and co-word network analysis was employed to identify the meaning at a micro level. First, the period of the First Republic was divided into two phases: the former period(1948-1955) and the latter period(1956-1960). The discourse analysis revealed four domestic discourses(Constitutional Amendment, Politics, Social Situation, and Election) and four international discourses(Maritime Sovereignty, World-Cold War, World-Independence, and the Division of Korea). The focus of the discourse shifted from international(the former) to domestic(the latter), with a particular emphasis on the discourse of election. The meaning analysis, at first indicated that both periods reflect an awareness of popular sovereignty and a recognition of deficiencies in its exercise. During the former period, 'Sovereignty' was perceived to be transferred and restored, but to be infringed and restricted especially in terms of territory. In the latter, ‘Sovereignty’ became a matter of defense and struggle with election being presented as the means of its exercise, thereby imparting proactivity to the concept.
This paper aims to thoroughly introduce the design and construction processes of two datasets related to Yi Sang's short stories: the Yi Sang Short Story Basic Dataset and the Yi Sang Short Story Sense Dataset. Centered on 13 selected short stories, the Yi Sang Short Story Basic Dataset presents a machine-readable structure created through the annotation of meta-data at the sentence level, based on editions from Mineumsa and Somyeong Publishing. The Yi Sang Short Story Sense Dataset, constructed by the researcher, labels sensory information found within the texts, using a sensory classifi-cation model that categorizes perceptions broadly into physical and psychological senses. This model further subdivides sensory details into four hierarchical levels, enabling nuanced, sentence-level labeling. The constructed datasets serve as practical foundations for conducting computational analyses of sensory patterns in Yi Sang’s short stories, as well as for other analytical methodologies such as emotion analysis, and further provide the potential for distant reading.
This study proposes the design and implementation of a subword-based morphological analyzer for automated analysis of modern Sino-Korean mixed texts. Current large-scale modern literature databases are difficult to process effectively with existing morphological analyzers due to their characteristics of mixed Sino-Korean characters and archaic Korean. To address this issue, we present a new approach using the sw_tokenizer of the kiwipiepy library based on subword tokenization. We implemented three models with different vocab sizes (32000, 48000, 64000) using approximately 2.3 million newspaper and magazine articles (about 771.5 million syllables) from 1890-1940 as training data. The experimental results show that larger vocab sizes better preserve the semantic units of compound Sino-Korean characters, and researchers can select appropriate analysis units according to their research purposes. This study contributes to digital humanities research by providing a practical tool for automated analysis of modern Sino-Korean mixed texts and suggests new directions for future research in this field.