# Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences

arXiv: https://arxiv.org/abs/2112.07497 · HTML: https://mlsanity.com/paper/2112.07497/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 27 references that are in the map.
- First posted on arXiv 14 Dec 2021.

## Built on by (most cited first, 2 of 2)

- [Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad](https://mlsanity.com/paper/2405.06760/) (2024)
- [Good Books are Complex Matters: Gauging Complexity Profiles Across Diverse Categories of Perceived Literary Quality](https://mlsanity.com/paper/2404.04022/) (2024)

## Abstract (arXiv)

We explore the correlation between the sentiment arcs of H. C. Andersen's fairy tales and their popularity, measured as their average score on the platform GoodReads. Specifically, we do not conceive a story's overall sentimental trend as predictive textitper se, but we focus on its coherence and predictability over time as represented by the arc's Hurst exponent. We find that degrading Hurst values tend to imply degrading quality scores, while a Hurst exponent between .55 and .65 might indicate a "sweet spot" for literary appreciation.