# The Emotion Dynamics of Literary Novels

arXiv: https://arxiv.org/abs/2403.02474 · HTML: https://mlsanity.com/paper/2403.02474/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 40 references that are in the map.
- First posted on arXiv 4 Mar 2024.

## Builds on (most cited first, 12 of 12)

- [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013)
- [Toward Gender-Inclusive Coreference Resolution](https://mlsanity.com/paper/1910.13913/) (2019)
- [The emotional arcs of stories are dominated by six basic shapes](https://mlsanity.com/paper/1606.07772/) (2016)
- [Word Affect Intensities](https://mlsanity.com/paper/1704.08798/) (2017)
- [Shirtless and Dangerous: Quantifying Linguistic Signals of Gender Bias in an Online Fiction Writing Community](https://mlsanity.com/paper/1603.08832/) (2016)
- [Emotion Dynamics in Movie Dialogues](https://mlsanity.com/paper/2103.01345/) (2021)
- [Practical and Ethical Considerations in the Effective use of Emotion and Sentiment Lexicons](https://mlsanity.com/paper/2011.03492/) (2020)
- [Evaluating Emotion Arcs Across Languages: Bridging the Global Divide in Sentiment Analysis](https://mlsanity.com/paper/2306.02213/) (2023)
- [Measuring Information Propagation in Literary Social Networks](https://mlsanity.com/paper/2004.13980/) (2020)
- [The Project Dialogism Novel Corpus: A Dataset for Quotation Attribution in Literary Texts](https://mlsanity.com/paper/2204.05836/) (2022)
- [Improving Automatic Quotation Attribution in Literary Novels](https://mlsanity.com/paper/2307.03734/) (2023)
- [A decomposition of book structure through ousiometric fluctuations in cumulative word-time](https://mlsanity.com/paper/2208.09496/) (2022)

## Built on by (most cited first, 12 of 12)

- [Feel the Difference? A Comparative Analysis of Emotional Arcs in Real and LLM-Generated CBT Sessions](https://mlsanity.com/paper/2508.20764/) (2025)
- [Once More, With Feeling: Measuring Emotion of Acting Performances in Contemporary American Film](https://mlsanity.com/paper/2411.10018/) (2024)
- [Continuous sentiment scores for literary and multilingual contexts](https://mlsanity.com/paper/2508.14620/) (2025)
- [Computational Narrative Understanding for Expressive Text-to-Speech](https://mlsanity.com/paper/2509.04072/) (2025)
- [S-VoCAL: A Dataset and Evaluation Framework for Inferring Speaking Voice Character Attributes in Literature](https://mlsanity.com/paper/2603.00958/) (2026)
- [Traversing Emotional Landscapes and Linguistic Patterns in Bernard-Marie Kolt`es' Plays: An NLP Perspective](https://mlsanity.com/paper/2410.09609/) (2024)
- [EditIQ: Automated Cinematic Editing of Static Wide-Angle Videos via Dialogue Interpretation and Saliency Cues](https://mlsanity.com/paper/2502.02172/) (2025)
- [Story2MIDI: Emotionally Aligned Music Generation from Text](https://mlsanity.com/paper/2512.02192/) (2025)
- [Quantifying Emotional Tone in Tolkien's The Hobbit: Dialogue Sentiment Analysis with RegEx, NRC-VAD, and Python](https://mlsanity.com/paper/2512.10865/) (2025)
- [Is Sentiment Banana-Shaped? Exploring the Geometry and Portability of Sentiment Concept Vectors](https://mlsanity.com/paper/2601.07995/) (2026)
- [Steering Emotional Dynamics for Art Therapy: Controllable Narrative Script Generation through Hierarchically Guided LLM Agents](https://mlsanity.com/paper/2606.16481/) (2026)
- [Fast and Accurate Quotation Attribution in Literary Texts](https://mlsanity.com/paper/2608.02359/) (2026)

## Abstract (arXiv)

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.