TaleStream: Supporting Story Ideation with Trope Knowledge

Abstract

Story ideation is a critical part of the story-writing process. It is challenging to support computationally due to its exploratory and subjective nature. Tropes, which are recurring narrative elements across stories, are essential in stories as they shape the structure of narratives and our understanding of them. In this paper, we propose to use tropes as an intermediate representation of stories to approach story ideation. We present TaleStream, a canvas system that uses tropes as building blocks of stories while providing steerable suggestions of story ideas in the form of tropes. Our trope suggestion methods leverage data from the tvtropes.org wiki. We find that 97% of the time, trope suggestions generated by our methods provide better story ideation materials than random tropes. Our system evaluation suggests that TaleStream can support writers' creative flow and greatly facilitates story development. Tropes, as a rich lexicon of narratives with available examples, play a key role in TaleStream and hold promise for story-creation support systems.

arXiv comment12 pages, 6 figures, 3 tables

References in corpus (10)

• Scikit-learn: Machine Learning in Python
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• PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration
• Script2Screen: Supporting Dialogue Scriptwriting with Interactive Audiovisual Generation