UWB at IEST 2018: Emotion Prediction in Tweets with Bidirectional Long Short-Term Memory Neural Network
2018-10-01WS 2018Unverified0· sign in to hype
Pavel P{\v{r}}ib{\'a}{\v{n}}, Ji{\v{r}}{\'\i} Mart{\'\i}nek
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This paper describes our system created for the WASSA 2018 Implicit Emotion Shared Task. The goal of this task is to predict the emotion of a given tweet, from which a certain emotion word is removed. The removed word can be sad, happy, disgusted, angry, afraid or a synonym of one of them. Our proposed system is based on deep-learning methods. We use Bidirectional Long Short-Term Memory (BiLSTM) with word embeddings as an input. Pre-trained DeepMoji model and pre-trained emoji2vec emoji embeddings are also used as additional inputs. Our System achieves 0.657 macro F1 score and our rank is 13th out of 30.