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BookNet: Building A Dataset of Narrative Features

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Partially supported by a NULab Seedling Grant and by an American Rescue Plan award.

In this research project, we’re hoping to fill a gap in quantitative narrative research by developing and introducing a new method for constructing “narrative experience” outcomes data. Specifically, we’re aiming to develop a new, standardized survey that we can administer at scale to create common experience-related metrics that one can use to compare movies across an unprecedentedly rich array of dimensions. We’re working with a small team to design and test a survey on how narratives are experienced (“How fast-paced was the middle of the story?”; “How closely did you identify with the main character?”; “Did the world of the story feel real?”) using movies.

In its final form, we would hope that this survey-based would enable groundbreaking new research on narratives along two new dimensions. First, we would hope that the existence of common metrics across stories will allow for innovative new descriptive and historical analysis of how stories have changed over time, how viewers’ preferences differ across geographies, and how companies and institutions might better tailor their narrative approaches to communicate better, or to evaluate stories better. Second, we plan to leverage these data to build and validate new, innovative approaches to quantifying narrative attributes and measuring narrative speed, cohesion and flow.

Further work on this project will continue under the Impact Engine program.

Principal Investigators:

Yakov Bart, Faculty, Business; Samsun Knight, Postdoctoral Researcher, Business

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