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ACL Findings2024

The Emotion Dynamics of Literary Novels

Krishnapriya Vishnubhotla, Adam Hammond, Graeme Hirst, Saif M. Mohammad

Abstract

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.

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Builds on4

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  3. Evaluating Emotion Arcs Across Languages: Bridging the Global Divide in Sentiment AnalysisDaniela Teodorescu, Saif M. MohammadEMNLP Findings 2023 · 5 citations
  4. Measuring Information Propagation in Literary Social NetworksMatthew Sims, David BammanEMNLP 2020 · 2 citations

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