Abstract
Everyone in a civilized society grows up by reading stories. Fictions, including those for children, are an important type of stories, as they reflect social and cultural reality to some degree. The plot, the figures, and the environment of a fiction are the three main elements of a fiction. In particular, the development of the plot is pivotal for a fiction to be successful. It is now generally thought that sentiment dynamics of the fiction can well reflect the plot development. With the availability of a number of algorithms to automatically obtain the sentiment dynamics of a fiction, it has become increasingly desirable to fully understand its sentiment dynamics. This motivates us to use random fractal theory to study a set of popular children’s fictions, The Chronicles of Narnia, written by the famed author, C.S. Lewis. We find the sentiment dynamics of each novel of the series possesses persistent long-range correlations, characterized by a Hurst parameter larger than 1/2. This has offered a mechanism to understand why many sentiment dynamics occurring naturally in a society or imagined by an author of a fiction can arouse strong emotions in humans. Interestingly, the value of the Hurst parameter for the series is strongly positively correlated with the score of the novels from Goodreads, suggesting that the scaling law governing sentiment dynamics can be used to objectively appraise the optimality of a fiction.
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References
Cambria, E.: Affective computing and sentiment analysis. IEEE Intell. Syst. 31(2), 102–107 (2016)
Cambria, E., Schuller, B., Xia, Y., et al.: New avenues in opinion mining and sentiment analysis. IEEE Intell. Syst. 28(2), 15–21 (2013)
Frankenstein, W., Joseph, K., Carley, K.M.: Contextual sentiment analysis. In: Xu, K., Reitter, D., Lee, D., Osgood, N. (eds.) International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, pp. 291–300. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39931-7_28
Archer, J., Jockers, M.: The Bestseller Code. St. Martins Press, New York (2016)
Jockers, M.: Syuzhet: extracts sentiment and sentiment-derived plot arcs from text (2015)
Lebovitch, L.S., Shehadeh, L.A.: Introduction to fractals. In: Rileyand, M.A., Van Orden, G.C. (eds.) Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences, pp. 178–266 (2005). http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jsp. Accessed 28 June 2012
Riley, M.A., Bonnette, S., Kuznetsov, N., et al.: A tutorial introduction to adaptive fractal analysis. Front. Physiol. 3, 371 (2012)
Gao, J.B., Cao, Y.H., Tung, W.W., Hu, J.: Multiscale Analysis of Complex Time Series: Integration of Chaos and Random Fractal Theory, and Beyond. Wiley, Hoboken (2007)
Gao, J., Hu, J., Tung, W.: Facilitating joint chaos and fractal analysis of biosignals through nonlinear adaptive filtering. PLoS ONE 6(9), e24331 (2011)
Gao, J., Fang, P., Liu, F.: Empirical scaling law connecting persistence and severity of global terrorism. Phys. A Stat. Mech. Appl. 482, 74–86 (2017)
Grossman, L.: All-TIME 100 Novels: The Lion, The Witch and the Wardrobe. Time, 16 October 2005. Accessed 25 May 2010
BBC - The Big Read. BBC, April 2003. Accessed 19 Oct 2012
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Dai, K., Ma, M., Gao, J. (2018). Sentiment Dynamics of The Chronicles of Narnia and Their Ranking. In: Thomson, R., Dancy, C., Hyder, A., Bisgin, H. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2018. Lecture Notes in Computer Science(), vol 10899. Springer, Cham. https://doi.org/10.1007/978-3-319-93372-6_24
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DOI: https://doi.org/10.1007/978-3-319-93372-6_24
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