Linguistic Features of Helpfulness in Automated Support for Creative Writing

Melissa Roemmele, Andrew Gordon


Abstract
We examine an emerging NLP application that supports creative writing by automatically suggesting continuing sentences in a story. The application tracks users’ modifications to generated sentences, which can be used to quantify their “helpfulness” in advancing the story. We explore the task of predicting helpfulness based on automatically detected linguistic features of the suggestions. We illustrate this analysis on a set of user interactions with the application using an initial selection of features relevant to story generation.
Anthology ID:
W18-1502
Volume:
Proceedings of the First Workshop on Storytelling
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venues:
NAACL | Story-NLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
14–19
Language:
URL:
https://www.aclweb.org/anthology/W18-1502
DOI:
10.18653/v1/W18-1502
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-1502.pdf