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Link to original content: https://doi.org/10.3115/v1/p15-1100
Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment - ACL Anthology

Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment

Byron C. Wallace, Do Kook Choe, Eugene Charniak


Anthology ID:
P15-1100
Volume:
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
July
Year:
2015
Address:
Beijing, China
Editors:
Chengqing Zong, Michael Strube
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1035–1044
Language:
URL:
https://aclanthology.org/P15-1100
DOI:
10.3115/v1/P15-1100
Bibkey:
Cite (ACL):
Byron C. Wallace, Do Kook Choe, and Eugene Charniak. 2015. Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1035–1044, Beijing, China. Association for Computational Linguistics.
Cite (Informal):
Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment (Wallace et al., ACL-IJCNLP 2015)
Copy Citation:
PDF:
https://aclanthology.org/P15-1100.pdf