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        <title>Incorporating Topic Aspects for Online Comment Convincingness Evaluation</title>
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    <name type="personal">
        <namePart type="given">Yunfan</namePart>
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    <abstract>In this paper, we propose to incorporate topic aspects information for online comments convincingness evaluation. Our model makes use of graph convolutional network to utilize implicit topic information within a discussion thread to assist the evaluation of convincingness of each single comment. In order to test the effectiveness of our proposed model, we annotate topic information on top of a public dataset for argument convincingness evaluation. Experimental results show that topic information is able to improve the performance for convincingness evaluation. We also make a move to detect topic aspects automatically.</abstract>
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%0 Conference Proceedings
%T Incorporating Topic Aspects for Online Comment Convincingness Evaluation
%A Gu, Yunfan
%A Wei, Zhongyu
%A Xu, Maoran
%A Fu, Hao
%A Liu, Yang
%A Huang, Xuanjing
%Y Slonim, Noam
%Y Aharonov, Ranit
%S Proceedings of the 5th Workshop on Argument Mining
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F gu-etal-2018-incorporating
%X In this paper, we propose to incorporate topic aspects information for online comments convincingness evaluation. Our model makes use of graph convolutional network to utilize implicit topic information within a discussion thread to assist the evaluation of convincingness of each single comment. In order to test the effectiveness of our proposed model, we annotate topic information on top of a public dataset for argument convincingness evaluation. Experimental results show that topic information is able to improve the performance for convincingness evaluation. We also make a move to detect topic aspects automatically.
%R 10.18653/v1/W18-5212
%U https://aclanthology.org/W18-5212
%U https://doi.org/10.18653/v1/W18-5212
%P 97-104

Markdown (Informal)

[Incorporating Topic Aspects for Online Comment Convincingness Evaluation](https://aclanthology.org/W18-5212) (Gu et al., ArgMining 2018)

• Incorporating Topic Aspects for Online Comment Convincingness Evaluation (Gu et al., ArgMining 2018)

ACL

• Yunfan Gu, Zhongyu Wei, Maoran Xu, Hao Fu, Yang Liu, and Xuanjing Huang. 2018. Incorporating Topic Aspects for Online Comment Convincingness Evaluation. In Proceedings of the 5th Workshop on Argument Mining, pages 97–104, Brussels, Belgium. Association for Computational Linguistics.