Evaluating the extent to which computer-produced stories are structured like human-invented narratives can be an important component of the quality of a story plot. In this paper, we report on an empirical experiment in which human subjects have invented short plots in a constrained scenario. The stories were annotated according to features commonly found in existing automatic story generators. The annotation was designed to measure the proportion and relations of story components that should be used in automatic computational systems for matching human behaviour. Results suggest that there are relatively common patterns that can be used as input data for identifying similarity to human-invented stories in automatic storytelling systems. The found patterns are in line with narratological models, and the results provide numerical quantification and layout of story components. The proposed method of story analysis is tested over two additional sources, the ROCStories corpus and stories generated by automated storytellers, to illustrate the valuable insights that may be derived from them.

中文翻译：

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人类短篇小说的定量特征作为自动讲故事的衡量标准

评估计算机制作的故事在多大程度上像人类发明的叙事一样结构化，可以成为故事情节质量的重要组成部分。在本文中，我们报告了一项实证实验，其中人类受试者在受限场景中发明了短情节。这些故事是根据现有自动故事生成器中常见的特征进行注释的。该注释旨在衡量应该在自动计算系统中用于匹配人类行为的故事组件的比例和关系。结果表明，在自动讲故事系统中，有相对常见的模式可用作识别与人类发明故事的相似性的输入数据。发现的模式符合叙事学模型，结果提供了故事组件的数值量化和布局。所提出的故事分析方法在两个额外的来源上进行了测试，ROCStories 语料库和由自动讲故事的人生成的故事，以说明可能从中得出的有价值的见解。