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        <title>Detecting Good Arguments in a Non-Topic-Specific Way: An Oxymoron?</title>
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        <namePart type="given">Beata</namePart>
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    <abstract>Automatic identification of good arguments on a controversial topic has applications in civics and education, to name a few. While in the civics context it might be acceptable to create separate models for each topic, in the context of scoring of students’ writing there is a preference for a single model that applies to all responses. Given that good arguments for one topic are likely to be irrelevant for another, is a single model for detecting good arguments a contradiction in terms? We investigate the extent to which it is possible to close the performance gap between topic-specific and across-topics models for identification of good arguments.</abstract>
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    <identifier type="doi">10.18653/v1/P17-2038</identifier>
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%0 Conference Proceedings
%T Detecting Good Arguments in a Non-Topic-Specific Way: An Oxymoron?
%A Beigman Klebanov, Beata
%A Gyawali, Binod
%A Song, Yi
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F beigman-klebanov-etal-2017-detecting
%X Automatic identification of good arguments on a controversial topic has applications in civics and education, to name a few. While in the civics context it might be acceptable to create separate models for each topic, in the context of scoring of students’ writing there is a preference for a single model that applies to all responses. Given that good arguments for one topic are likely to be irrelevant for another, is a single model for detecting good arguments a contradiction in terms? We investigate the extent to which it is possible to close the performance gap between topic-specific and across-topics models for identification of good arguments.
%R 10.18653/v1/P17-2038
%U https://aclanthology.org/P17-2038
%U https://doi.org/10.18653/v1/P17-2038
%P 244-249

Markdown (Informal)

[Detecting Good Arguments in a Non-Topic-Specific Way: An Oxymoron?](https://aclanthology.org/P17-2038) (Beigman Klebanov et al., ACL 2017)

• Detecting Good Arguments in a Non-Topic-Specific Way: An Oxymoron? (Beigman Klebanov et al., ACL 2017)

ACL

• Beata Beigman Klebanov, Binod Gyawali, and Yi Song. 2017. Detecting Good Arguments in a Non-Topic-Specific Way: An Oxymoron?. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 244–249, Vancouver, Canada. Association for Computational Linguistics.