NLP和HCI视角下的叙事数据集

S. Sultana, Renwen Zhang, Hajin Lim, Maria Antoniak
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引用次数: 2

摘要

在这篇短文中,我们比较了NLP和HCI中收集叙事数据的现有价值体系和方法。在这些平行讨论的基础上,我们揭示了一些流行的NLP数据集类型所面临的挑战,我们讨论了这些挑战与广泛使用的基于叙事的HCI研究方法的关系;我们强调了NLP方法可以扩大定性叙事研究的要点。我们特别指出,在研究叙事时,语境性、位置性、数据集大小和开放式研究设计是差异的中心点和合作的窗口。通过叙述的用例,这项工作有助于通过推测混合方法连接NLP和HCI的可能性进行更大的对话。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Narrative Datasets through the Lenses of NLP and HCI
In this short paper, we compare existing value systems and approaches in NLP and HCI for collecting narrative data. Building on these parallel discussions, we shed light on the challenges facing some popular NLP dataset types, which we discuss these in relation to widely-used narrative-based HCI research methods; and we highlight points where NLP methods can broaden qualitative narrative studies. In particular, we point towards contextuality, positionality, dataset size, and open research design as central points of difference and windows for collaboration when studying narratives. Through the use case of narratives, this work contributes to a larger conversation regarding the possibilities for bridging NLP and HCI through speculative mixed-methods.
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