Abstract This study investigates the relationships among emotional arcs, thematic topics, and narrative arcs in a corpus of 100 English fairy tales drawn from Project Gutenberg. Sentence-level sentiment scores were computed using Flair and then aggregated to construct emotional arcs, which captured consistent patterns of affective change throughout each narrative. Thematic topics were extracted by applying Latent Dirichlet Allocation to TF-IDF vectors and were subsequently validated using perplexity, coherence metrics, and expert review. Narrative arcs were annotated based on Freytag’s five-stage model, which provided a structural framework to trace story progression from exposition to resolution. The analysis demonstrates that: (1) fairy tales exhibit six distinct shapes of emotional arcs; (2) a reciprocal relationship exists between these emotional arcs and the thematic topics of “Fate” and “Growth”; (3) emotional arcs function as a covert driving force that underlies the development of narrative arcs.
Yang et al. (Sat,) studied this question.