FracTale: Assessing the Correlation Between Narrative Beauty and Self-Similarity in Grimm’s Folktales

This work presents an assessment of the correlation between self-similarity and literary quality in Grimm’s folktales. It examines text patterns at multiple levels (episodes, sentences, clauses) using homothety to evaluate similarity distributions across scales. The research employs Moran’s I for spatial autocorrelation analysis and the Hurst Exponent to quantify the long-term memory of informativeness values based on Dependency Distance and Eventfulness, thus modeling texts as both spatial objects and time-series. The study defines literary quality by a tale’s presence in the "Best fairytales" list from the corpus source website. The results are validated against randomly generated- and Europeana stories.