IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets
This is an incremental approach to a domain-specific problem in natural language processing for social media analysis.
The authors tackled irony detection in English tweets using a multi-layered bidirectional LSTM without external features, achieving better performance than the baseline on the validation set but showing limited generalization on the test set.
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.