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An Interaction Model Based on Narrative Programs to Improve Understanding and Contribution to Non-Linear Narratives

机译:基于叙事计划的互动模型,提高对非线性叙事的理解和贡献

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Collaborative creation of stories poses new challenges to the authoring task. Being able to comprehend a large non-linear information space and to take into account inputs from other creators are important to contribute meaningfully and consistently. This work presents a model based on the classic semiotics concept of "narrative programs" to structure and present the information with the purpose of making non-linearity more accessible, facilitating contribution, and inspiring creative opportunities. We introduce a prototype that implements this model, and use it in an experiment to explore how users read a non-linear story, understand it, and contribute to it. Results show how users identified the main characters and related them to their narrative programs achieving high levels of comprehension, which the correspondence between comprehension and contribution consistency was, and that the users expanded the narrative from multiple points of view.
机译:对故事的协同创建对创作任务构成了新的挑战。能够理解大型非线性信息空间,并考虑到其他创造者的意见是有意义的且始终如一地贡献的重要性。这项工作提出了一种基于经典符号学概念的“叙事计划”的模型,以构造,并呈现出于使非线性更可获得的信息,促进贡献和鼓舞人心的创造性机会的信息。我们介绍了一种实现此模型的原型,并在实验中使用它来探索用户如何阅读非线性故事,了解它,并为其贡献。结果表明,用户如何确定主角并将其与其叙述计划相关,以实现高度理解的叙述,这是理解和贡献一致性之间的对应关系,并且用户从多个角度扩展了叙述。

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