@inproceedings{yoder-etal-2021-fanfictionnlp,
title = "{F}anfiction{NLP}: A Text Processing Pipeline for Fanfiction",
author = "Yoder, Michael and
Khosla, Sopan and
Shen, Qinlan and
Naik, Aakanksha and
Jin, Huiming and
Muralidharan, Hariharan and
Ros{\'e}, Carolyn",
editor = "Akoury, Nader and
Brahman, Faeze and
Chaturvedi, Snigdha and
Clark, Elizabeth and
Iyyer, Mohit and
Martin, Lara J.",
booktitle = "Proceedings of the Third Workshop on Narrative Understanding",
month = jun,
year = "2021",
address = "Virtual",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.nuse-1.2",
doi = "10.18653/v1/2021.nuse-1.2",
pages = "13--23",
abstract = "Fanfiction presents an opportunity as a data source for research in NLP, education, and social science. However, answering specific research questions with this data is difficult, since fanfiction contains more diverse writing styles than formal fiction. We present a text processing pipeline for fanfiction, with a focus on identifying text associated with characters. The pipeline includes modules for character identification and coreference, as well as the attribution of quotes and narration to those characters. Additionally, the pipeline contains a novel approach to character coreference that uses knowledge from quote attribution to resolve pronouns within quotes. For each module, we evaluate the effectiveness of various approaches on 10 annotated fanfiction stories. This pipeline outperforms tools developed for formal fiction on the tasks of character coreference and quote attribution",
}
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<abstract>Fanfiction presents an opportunity as a data source for research in NLP, education, and social science. However, answering specific research questions with this data is difficult, since fanfiction contains more diverse writing styles than formal fiction. We present a text processing pipeline for fanfiction, with a focus on identifying text associated with characters. The pipeline includes modules for character identification and coreference, as well as the attribution of quotes and narration to those characters. Additionally, the pipeline contains a novel approach to character coreference that uses knowledge from quote attribution to resolve pronouns within quotes. For each module, we evaluate the effectiveness of various approaches on 10 annotated fanfiction stories. This pipeline outperforms tools developed for formal fiction on the tasks of character coreference and quote attribution</abstract>
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%0 Conference Proceedings
%T FanfictionNLP: A Text Processing Pipeline for Fanfiction
%A Yoder, Michael
%A Khosla, Sopan
%A Shen, Qinlan
%A Naik, Aakanksha
%A Jin, Huiming
%A Muralidharan, Hariharan
%A Rosé, Carolyn
%Y Akoury, Nader
%Y Brahman, Faeze
%Y Chaturvedi, Snigdha
%Y Clark, Elizabeth
%Y Iyyer, Mohit
%Y Martin, Lara J.
%S Proceedings of the Third Workshop on Narrative Understanding
%D 2021
%8 June
%I Association for Computational Linguistics
%C Virtual
%F yoder-etal-2021-fanfictionnlp
%X Fanfiction presents an opportunity as a data source for research in NLP, education, and social science. However, answering specific research questions with this data is difficult, since fanfiction contains more diverse writing styles than formal fiction. We present a text processing pipeline for fanfiction, with a focus on identifying text associated with characters. The pipeline includes modules for character identification and coreference, as well as the attribution of quotes and narration to those characters. Additionally, the pipeline contains a novel approach to character coreference that uses knowledge from quote attribution to resolve pronouns within quotes. For each module, we evaluate the effectiveness of various approaches on 10 annotated fanfiction stories. This pipeline outperforms tools developed for formal fiction on the tasks of character coreference and quote attribution
%R 10.18653/v1/2021.nuse-1.2
%U https://aclanthology.org/2021.nuse-1.2
%U https://doi.org/10.18653/v1/2021.nuse-1.2
%P 13-23
Markdown (Informal)
[FanfictionNLP: A Text Processing Pipeline for Fanfiction](https://aclanthology.org/2021.nuse-1.2) (Yoder et al., NUSE-WNU 2021)
ACL
- Michael Yoder, Sopan Khosla, Qinlan Shen, Aakanksha Naik, Huiming Jin, Hariharan Muralidharan, and Carolyn Rosé. 2021. FanfictionNLP: A Text Processing Pipeline for Fanfiction. In Proceedings of the Third Workshop on Narrative Understanding, pages 13–23, Virtual. Association for Computational Linguistics.