TY - CONF
T1 - Sentiment Dynamics of Success
T2 - Fractal Scaling of Story Arcs Predicts Reader Preferences
AU - Bizzoni, Yuri
AU - Peura, Telma
AU - Thomsen, Mads Rosendahl
AU - Nielbo, Kristoffer Laigaard
PY - 2021/12/14
Y1 - 2021/12/14
N2 - 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 \textit{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.
AB - 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 \textit{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.
UR - https://arxiv.org/abs/2112.07497
M3 - Paper
ER -