How quantifying the shape of stories predicts their success

Olivier Toubia (), Jonah Berger and Jehoshua Eliashberg
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Olivier Toubia: Marketing Division, Columbia Business School, Columbia University, New York, NY 10027
Jonah Berger: Marketing Department, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104
Jehoshua Eliashberg: Marketing Department, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 26, e2011695118

Abstract: Narratives, and other forms of discourse, are powerful vehicles for informing, entertaining, and making sense of the world. But while everyday language often describes discourse as moving quickly or slowly, covering a lot of ground, or going in circles, little work has actually quantified such movements or examined whether they are beneficial. To fill this gap, we use several state-of-the-art natural language-processing and machine-learning techniques to represent texts as sequences of points in a latent, high-dimensional semantic space. We construct a simple set of measures to quantify features of this semantic path, apply them to thousands of texts from a variety of domains (i.e., movies, TV shows, and academic papers), and examine whether and how they are linked to success (e.g., the number of citations a paper receives). Our results highlight some important cross-domain differences and provide a general framework that can be applied to study many types of discourse. The findings shed light on why things become popular and how natural language processing can provide insight into cultural success.

Keywords: discourse; natural language processing; cultural success; cultural analytics (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (7)

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