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 multilayered 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.
Cite
CITATION STYLE
Marrese-Taylor, E., Ilic, S., Balazs, J. A., Prendinger, H., & Matsuo, Y. (2018). IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets. In NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 537–540). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1087
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