Mapping thematic patterns in Indonesian novels through concept mining and computational linguistics - Kun Andyan Anindita; Susan Hockey; Tomi Wahyu Septarianto (Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU), 2026)
Background: The expansion of Indonesian novels across historical periods has produced complex and overlapping thematic formations that remain difficult to map systematically using conventional close-reading approaches. Objective: This study aims to identify dominant themes, trace their temporal shifts, and examine conceptual overlap among Indonesian novels through a computational framework. Method: Employing a digital humanities approach, the study analyzes a corpus of 30 Indonesian novels (1920-2022) using concept mining, CF-IDF weighting, semantic similarity measurement, and network analysis. Results: The findings reveal dominant thematic clusters centered on social inequality, nationalism, gender, religion, and modernization; clear temporal shifts in thematic emphasis across literary periods; and dense conceptual overlap, with social inequality functioning as a central thematic hub. Theme–theme projection and betweenness centrality analysis further demonstrate that thematic meaning emerges through relational structures rather than isolated categories. Implication: These results strengthen empirical literary analysis by integrating computational rigor with interpretive criticism. Novelty: This study introduces a replicable, network-based thematic mapping model for Indonesian novels, advancing computational literary studies in the Indonesian context.