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Narrative Information Theory
November 19, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Lion Schulz, Miguel PatrΓcio, Daan Odijk
arXiv ID
2411.12907
Category
cs.MM: Multimedia
Cross-listed
cs.IT
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We propose an information-theoretic framework to measure narratives, providing a formalism to understand pivotal moments, cliffhangers, and plot twists. This approach offers creatives and AI researchers tools to analyse and benchmark human- and AI-created stories. We illustrate our method in TV shows, showing its ability to quantify narrative complexity and emotional dynamics across genres. We discuss applications in media and in human-in-the-loop generative AI storytelling.
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