Claims are the building blocks of arguments and the reasons underpinning opinions, thus analyzing claims is important for both argumentation mining and opinion mining. We propose a framework for representing claims as microstructures, which express the beliefs, judgments, and policies about the relations between domain-specific concepts. In a proof-of-concept study, we manually build microstructures for over 800 claims extracted from an online debate. We test the so-obtained microstructures on the task of claim stance classification, achieving considerable improvements over text-based baselines.
CITATION STYLE
Boltužić, F., & Šnajder, J. (2017). Toward stance classification based on claim microstructures. In EMNLP 2017 - 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2017 - Proceedings of the Workshop (pp. 74–80). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-5210
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