2018
EMNLP
EMNLP 2018
Incorporating Topic Aspects for Online Comment Convincingness Evaluation
Abstract
AbstractIn 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.
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Interdisciplinary Bridge
- Artificial Intelligence and Computer Science and Data Science & Analytics and Natural Language Processing