  In this paper, we describe the system submitted for the SemEval 2018 Task 3
(Irony detection in English tweets) Subtask A by the team Binarizer. Irony
detection is a key task for many natural language processing works. Our method
treats ironical tweets to consist of smaller parts containing different
emotions. We break down tweets into separate phrases using a dependency parser.
We then embed those phrases using an LSTM-based neural network model which is
pre-trained to predict emoticons for tweets. Finally, we train a
fully-connected network to achieve classification.
