Abstract
We created a corpus of utterances that attempt to save face from parliamentary debates and use it to automatically analyze the language of reputation defence. Our proposed model that incorporates information regarding threats to reputation can predict reputation defence language with high confidence. Further experiments and evaluations on different datasets show that the model is able to generalize to new utterances and can predict the language of reputation defence in a new dataset.- Anthology ID:
- W18-5214
- Volume:
- Proceedings of the 5th Workshop on Argument Mining
- Month:
- November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Noam Slonim, Ranit Aharonov
- Venue:
- ArgMining
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 111–120
- Language:
- URL:
- https://aclanthology.org/W18-5214
- DOI:
- 10.18653/v1/W18-5214
- Cite (ACL):
- Nona Naderi and Graeme Hirst. 2018. Using context to identify the language of face-saving. In Proceedings of the 5th Workshop on Argument Mining, pages 111–120, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Using context to identify the language of face-saving (Naderi & Hirst, ArgMining 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/W18-5214.pdf