Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences
Yuri Bizzoni, Telma Peura, Mads Rosendahl Thomsen, Kristoffer Nielbo
Abstract
e 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 per 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.- Anthology ID:
- 2021.nlp4dh-1.1
- Volume:
- Proceedings of the Workshop on Natural Language Processing for Digital Humanities
- Month:
- December
- Year:
- 2021
- Address:
- NIT Silchar, India
- Editors:
- Mika Hämäläinen, Khalid Alnajjar, Niko Partanen, Jack Rueter
- Venue:
- NLP4DH
- SIG:
- Publisher:
- NLP Association of India (NLPAI)
- Note:
- Pages:
- 1–6
- Language:
- URL:
- https://aclanthology.org/2021.nlp4dh-1.1
- DOI:
- Cite (ACL):
- Yuri Bizzoni, Telma Peura, Mads Rosendahl Thomsen, and Kristoffer Nielbo. 2021. Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences. In Proceedings of the Workshop on Natural Language Processing for Digital Humanities, pages 1–6, NIT Silchar, India. NLP Association of India (NLPAI).
- Cite (Informal):
- Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences (Bizzoni et al., NLP4DH 2021)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/2021.nlp4dh-1.1.pdf