Using context to identify the language of face-saving

Nona Naderi, Graeme Hirst


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
Bibkey:
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)
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PDF:
https://aclanthology.org/W18-5214.pdf