In this paper we present our model on the task of emotion detection in
textual conversations in SemEval-2019. Our model extends the Recurrent
Convolutional Neural Network (RCNN) by using external fined-tuned word
representations and DeepMoji sentence representations. We also explored several
other competitive pre-trained word and sentence representations including ELMo,
BERT and InferSent but found inferior performances. In addition, we conducted
extensive sensitivity analysis, which empirically shows that our model is
relatively robust to hyper-parameters. Our model requires no handcrafted
features or emotion lexicons but achieved good performance with a test micro-F1
of 0.7463.

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