IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets

Edison Marrese-Taylor, Suzana Ilic, Jorge Balazs, Helmut Prendinger, Yutaka Matsuo

Abstract
In this paper we introduce our system for the task of Irony detection in English tweets, a part of SemEval 2018. We propose representation learning approach that relies on a multi-layered bidirectional LSTM, without using external features that provide additional semantic information. Although our model is able to outperform the baseline in the validation set, our results show limited generalization power over the test set. Given the limited size of the dataset, we think the usage of more pre-training schemes would greatly improve the obtained results.
Anthology ID:
S18-1087
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
537–540
Language:
URL:
https://aclanthology.org/S18-1087
DOI:
10.18653/v1/S18-1087
Bibkey:
Cite (ACL):
Edison Marrese-Taylor, Suzana Ilic, Jorge Balazs, Helmut Prendinger, and Yutaka Matsuo. 2018. IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 537–540, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets (Marrese-Taylor et al., SemEval 2018)
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PDF:
https://preview.aclanthology.org/naacl24-info/S18-1087.pdf
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