The Emotion Dynamics of Literary Novels
This work addresses a gap in computational literary analysis for researchers and enthusiasts by moving beyond single-story arcs to character-level emotion dynamics, though it is incremental in its methodological approach.
The paper tackled the problem of analyzing emotional trajectories in literary novels by distinguishing between narration and character dialogue, finding that these express disparate emotions and that character-specific arcs better capture story commonalities or differences.
Stories are rich in the emotions they exhibit in their narratives and evoke in the readers. The emotional journeys of the various characters within a story are central to their appeal. Computational analysis of the emotions of novels, however, has rarely examined the variation in the emotional trajectories of the different characters within them, instead considering the entire novel to represent a single story arc. In this work, we use character dialogue to distinguish between the emotion arcs of the narration and the various characters. We analyze the emotion arcs of the various characters in a dataset of English literary novels using the framework of Utterance Emotion Dynamics. Our findings show that the narration and the dialogue largely express disparate emotions through the course of a novel, and that the commonalities or differences in the emotional arcs of stories are more accurately captured by those associated with individual characters.