INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter

Delia Irazú Hernández Farías, Fernando Sánchez-Vega, Manuel Montes-y-Gómez, Paolo Rosso


Abstract
This paper describes an ensemble approach to the SemEval-2018 Task 3. The proposed method is composed of two renowned methods in text classification together with a novel approach for capturing ironic content by exploiting a tailored lexicon for irony detection. We experimented with different ensemble settings. The obtained results show that our method has a good performance for detecting the presence of ironic content in Twitter.
Anthology ID:
S18-1097
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venues:
SemEval | *SEM
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
594–599
Language:
URL:
https://aclanthology.org/S18-1097
DOI:
10.18653/v1/S18-1097
Bibkey:
Cite (ACL):
Delia Irazú Hernández Farías, Fernando Sánchez-Vega, Manuel Montes-y-Gómez, and Paolo Rosso. 2018. INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 594–599, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter (Hernández Farías et al., SemEval-*SEM 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/S18-1097.pdf