Text Mining and Fuzzy Logic in Literary Analysis: A Computational Study of The Book of Dede Korkut Using Voyant Tools

Abstract

This study explores the computational and stylistic features of The Book of Dede Korkut using Voyant Tools and fuzzy logic. The research applies Corpus Linguistics and draws on Kamal Abdulla and Rafik Aliev’s (2023) theoretical insights, highlighting how fuzzy logic, centered on uncertainty and symbolic reasoning, mirrors the non-linear nature of mythological storytelling. A corpus-based methodology was employed, analyzing sentence structures, co-occurrence patterns, and stylistic trends through visualization techniques such as word clouds and dispersion plots. Frequent terms included "logic" (239), "fuzzy" (203), "text" (112), "epos" (95), and "language" (94), with 3,213 unique word forms identified. The study demonstrates that combining text mining and fuzzy logic deepens the understanding of stylistic patterns and the complex organization of mythological narratives. Customized visual dashboards could improve VT’s usability for complex corpora, while collaboration with linguists and computational scientists is key to refining the application of fuzzy logic in textual analysis and advancing computational studies of traditional narratives.