AI RESEARCH
Hybrid topic modelling for computational close reading: Mapping narrative themes in Pushkin's Evgenij Onegin
arXiv CS.CL
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ArXi:2603.19940v1 Announce Type: new This study presents a hybrid topic modelling framework for computational literary analysis that integrates Latent Dirichlet Allocation (LDA) with sparse Partial Least Squares Discriminant Analysis (sPLS-DA) to model thematic structure and longitudinal dynamics in narrative poetry. As a, we analyse Evgenij Onegin-Aleksandr S. Pushkin's novel in verse-using an Italian translation, testing whether unsupervised and supervised lexical structures converge in a small-corpus setting.