How quantifying the shape of stories predicts their success.

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 nu

SUBMITTER: Toubia O 

PROVIDER: S-EPMC8256009 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature