Branching Narratives: Character Decision Points Detection

• URL: http://arxiv.org/abs/2405.07282v1
• Date: Sun, 12 May 2024 13:36:07 GMT
• Title: Branching Narratives: Character Decision Points Detection
• Authors: Alexey Tikhonov,
• Abstract summary: We propose a novel dataset based on CYOA-like games graphs to be used as a benchmark for such a task. We show how such a model can be applied to the existing text to produce linear segments divided by potential branching points.
• Score: 13.615681132633561
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: This paper presents the Character Decision Points Detection (CHADPOD) task, a task of identification of points within narratives where characters make decisions that may significantly influence the story's direction. We propose a novel dataset based on CYOA-like games graphs to be used as a benchmark for such a task. We provide a comparative analysis of different models' performance on this task, including a couple of LLMs and several MLMs as baselines, achieving up to 89% accuracy. This underscores the complexity of narrative analysis, showing the challenges associated with understanding character-driven story dynamics. Additionally, we show how such a model can be applied to the existing text to produce linear segments divided by potential branching points, demonstrating the practical application of our findings in narrative analysis.

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