@inproceedings{persing-ng-2017-lightly,
title = "Lightly-Supervised Modeling of Argument Persuasiveness",
author = "Persing, Isaac and
Ng, Vincent",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-1060",
pages = "594--604",
abstract = "We propose the first lightly-supervised approach to scoring an argument{'}s persuasiveness. Key to our approach is the novel hypothesis that lightly-supervised persuasiveness scoring is possible by explicitly modeling the major errors that negatively impact persuasiveness. In an evaluation on a new annotated corpus of online debate arguments, our approach rivals its fully-supervised counterparts in performance by four scoring metrics when using only 10{\%} of the available training instances.",
}
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%0 Conference Proceedings
%T Lightly-Supervised Modeling of Argument Persuasiveness
%A Persing, Isaac
%A Ng, Vincent
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F persing-ng-2017-lightly
%X We propose the first lightly-supervised approach to scoring an argument’s persuasiveness. Key to our approach is the novel hypothesis that lightly-supervised persuasiveness scoring is possible by explicitly modeling the major errors that negatively impact persuasiveness. In an evaluation on a new annotated corpus of online debate arguments, our approach rivals its fully-supervised counterparts in performance by four scoring metrics when using only 10% of the available training instances.
%U https://aclanthology.org/I17-1060
%P 594-604
Markdown (Informal)
[Lightly-Supervised Modeling of Argument Persuasiveness](https://aclanthology.org/I17-1060) (Persing & Ng, IJCNLP 2017)
ACL
- Isaac Persing and Vincent Ng. 2017. Lightly-Supervised Modeling of Argument Persuasiveness. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 594–604, Taipei, Taiwan. Asian Federation of Natural Language Processing.