A Hybrid AI and Computational Linguistics Framework for Thematic and Narrative Analysis in Literary Studies - Tohir Zuhdi; Taqwa Hariguna; Berlilana Berlilana (Politeknik Pertanian Negeri Samarinda, 2026)
This study aims to examine the integration of Artificial Intelligence (AI) and computational linguistics in thematic and narrative analysis of literary works, particularly within the framework of digital humanities. The background of this research arises from the limitations of manual methods, which tend to be time-consuming, subjective, and less effective when dealing with large text corpora. To address these challenges, the study adopts a quantitative approach using questionnaires tested for validity and reliability, involving 100 respondents consisting of educators and academics. Data were analyzed using the Wilcoxon test and Friedman test with the assistance of SPSS software. The findings reveal that narrative analysis received the highest appreciation compared to other variables, with a mean score of 48.32. The Wilcoxon test indicates that AI makes a significant contribution to supporting narrative analysis, while computational linguistics shows significant differences in both thematic and narrative analysis. The Friedman test further strengthens these findings by demonstrating significant differences among the variables, indicating that the integration of AI and computational linguistics provides a new methodological framework in literary studies. This research concludes that technological integration enriches literary analysis through more efficient, objective, and systematic approaches, although it still requires humanistic interpretation to maintain the validity of meaning. These findings are expected to provide both practical and theoretical contributions to the development of literary studies in the digital era