Conference Proceedings

Recognising agreement and disagreement between stances with reason comparing networks

C Xu, C Paris, S Nepal, R Sparks

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics | The Association for Computational Linguistics | Published : 2020


We identify agreement and disagreement between utterances that express stances towards a topic of discussion. Existing methods focus mainly on conversational settings, where dialogic features are used for (dis)agreement inference. We extend this scope and seek to detect stance (dis)agreement in a broader setting, where independent stance-bearing utterances, which prevail in many stance corpora and real-world scenarios, are compared. To cope with such non-dialogic utterances, we find that the reasons uttered to back up a specific stance can help predict stance (dis)agreements. We propose a reason comparing network (RCN) to leverage reason information for stance comparison. Empirical results o..

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University of Melbourne Researchers

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