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.
Cite
CITATION STYLE
Farías, D. I. H., Sánchez-Vega, F., Montes-Y-Gómez, M., & Rosso, P. (2018). INAOE-UPV at SemEval-2018 Task 3: An Ensemble Approach for Irony Detection in Twitter. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 594–599). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1097
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