Narrative Theory for Computational Narrative Understanding
Andrew Piper, Richard Jean So, David Bamman
摘要
Over the past decade, the field of natural language processing has developed a wide array of computational methods for reasoning about narrative, including summarization, commonsense inference, and event detection. While this work has brought an important empirical lens for examining narrative, it is by and large divorced from the large body of theoretical work on narrative within the humanities, social and cognitive sciences. In this position paper, we introduce the dominant theoretical frameworks to the NLP community, situate current research in NLP within distinct narratological traditions, and argue that linking computational work in NLP to theory opens up a range of new empirical questions that would both help advance our understanding of narrative and open up new practical applications.
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引用它的顶会 Paper12
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- Event-Location Tracking in Narratives: A Case Study on Holocaust TestimoniesEitan Wagner, Renana Keydar, Omri AbendEMNLP 2023 · 被引用 1 次
它引用的顶会 Paper4
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- Modeling Protagonist Emotions for Emotion-Aware StorytellingFaeze Brahman, Snigdha ChaturvediEMNLP 2020 · 被引用 5 次
- Suspense in Short Stories is Predicted By Uncertainty Reduction over Neural Story RepresentationDavid Wilmot, Frank KellerACL 2020 · 被引用 2 次
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