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Predicting User Choices in Interactive Narratives Using Indexter's Pairwise Event Salience Hypothesis

机译:使用索引的成对事件显着假设预测交互式叙述中的用户选择

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Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that when a past event shares one or more of these indices with the most recently narrated event, that past event is more salient, or easier to recall, than an event which shares none of them. In this study we demonstrate that we can predict user choices based on the salience of past events. Specifically, we investigate the hypothesis that when users are given a choice between two events in an interactive narrative, they are more likely to choose the one which makes the previous events in the story more salient according to this theory.
机译:索引是一个基于计划的叙述模型,包括关于叙事事件的显着性的认知科学理论。一对索引事件可以相互分享到五个指数:主角,时间,空间,因果和意向性。成对事件显着假设指出,当过去的事件与最近叙述的事件中的一个或多个索引共享其中一个或多个时,过去的事件更加突出,或者更容易回忆,而不是共享它们的事件。在这项研究中,我们证明我们可以根据过去事件的显着性来预测用户选择。具体而言,我们调查了这个假设,当用户在交互式叙述中的两个事件之间进行选择时,他们更有可能根据该理论选择使其在故事中更加突出的事件。

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