Abstract: This study o昀昀ers a fresh perspective on the Canon/Archive problem in literature through computational analysis. Following Tynianov’s understanding of literature, we adopt a dynamic approach to literature by proposing a model of literary variability using the Kullback-Leibler divergence. We retrieve key authors and works that shape the broad outlines of literary change. Our aim is to evaluate the importance of canonical authors on literary variability. We opt for a cohort-driven setup to analyze the variability contributed by a given text, focusing on speci昀椀c formal and semantic aspects of texts such as topics, lexicon, characterization, and chronotope. The 昀椀ndings reveal that canonical authors tend to contribute slightly more to literary change than those from the archive.
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