Our talk aims to examine a body of works by Yŏm Sang-sŏp (1897-1963), a major fiction writer and critic in South Korea, through digital and quantitative analyses. Famous for balancing between right and left-wing ideology and for his realistic writing style packed with witty punchlines, Yŏm portrayed Korean society during and after the colonial period (1910-1945). Unlike many Korean writers who relocated to the North, voluntarily or otherwise, or who died during or shortly after the Korean War (1950-1953), Yŏm was an eyewitness to the emergence and development of Korean literature in the South. It is thus unfortunate that the existing literature has so far focused on a small number of his canonical works. Here, we digitize as many of his fictional stories as possible and examine them via quantitative and computational methods. In the first half of the talk, we will discuss the results of corpus analysis, including word frequency, co-occurrence, and text similarity, and attempt to link them to the narrative structure. In the second half, we will examine Yŏm’s sequential novels published after the Korean War (1950-1953) through a network analysis of the main characters. This will demonstrate to us their various roles as links in an interconnected fictional universe. We hope that our presentation will reveal new possibilities for the application of digital approaches to authorial studies in Korean literature.
Jae-Yon Lee is an associate professor of modern Korean literature at Ulsan National Institute of Science and Technology (UNIST) in South Korea. His research interests include twentieth-century Korean fiction and criticism, periodical studies, and digital literary studies. He has published collaborative works on network analysis, corpus analysis, and word embedding. He recently translated Franco Moretti’s Graphs, Maps, Trees into Korean and is working on a book manuscript that analyzes Korean periodicals through quantitative approaches.
Namgi Han is a postdoctoral fellow of informatics at Ulsan National Institute of Science and Technology (UNIST) in South Korea. In 2021, he graduated from the Graduate University for Advanced Studies, SOKENDAI, in Japan. His research interests include natural language processing and neural network interpretability. He has recently published papers examining the performance of neural networks by applying linguistic knowledge to question answering systems. He currently assists with teaching digital humanities and AI-generated writing courses at UNIST.