The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task

February 07, 2017 ยท Declared Dead ยท ๐Ÿ› Conference on Computational Natural Language Learning

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Authors Roy Schwartz, Maarten Sap, Ioannis Konstas, Li Zilles, Yejin Choi, Noah A. Smith arXiv ID 1702.01841 Category cs.CL: Computation & Language Citations 120 Venue Conference on Computational Natural Language Learning Last Checked 4 months ago
Abstract
A writer's style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can lead to measurable differences in writing style. We present a case study based on the story cloze task (Mostafazadeh et al., 2016a), where annotators were assigned similar writing tasks with different constraints: (1) writing an entire story, (2) adding a story ending for a given story context, and (3) adding an incoherent ending to a story. We show that a simple linear classifier informed by stylistic features is able to successfully distinguish among the three cases, without even looking at the story context. In addition, combining our stylistic features with language model predictions reaches state of the art performance on the story cloze challenge. Our results demonstrate that different task framings can dramatically affect the way people write.
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