Sentiment analysis, particularly with the advent of large language models, is reshaping our understanding of narrative. Emotional arcs in both fictional and non-fictional narratives surface latent structures that challenge traditional notions of plot and character. One reason is that feature extraction correlates with passages often selected for close reading, suggesting the role of emotion in passage selection has been undertheorized. Case studies, moreover, show that common critiques of sentiment analysis are misplaced, and the method can identify and contrast cultural differences, locate translation effects, and illuminate collective emotional experiences. Both the strengths and limitations of sentiment analysis in understanding affect and emotion in literature are detailed to help address misconceptions. The method, as it turns out, now offers a powerful tool for highlighting emotional structure in narrative, complementing traditional literary analysis and reshaping our understanding of what constitutes a story. Sentiment analysis for literary studies asks us to reconsider not just how we analyze individual texts, but how we conceptualize the very nature of narrative itself.
Editors’ Choice: Beyond Plot: How Sentiment Analysis Reshapes Our Understanding of Narrative Structure
