  In this paper, we present the system we have used for the Implicit WASSA 2018
Implicit Emotion Shared Task. The task is to predict the emotion of a tweet of
which the explicit mentions of emotion terms have been removed. The idea is to
come up with a model which has the ability to implicitly identify the emotion
expressed given the context words. We have used a Gated Recurrent Neural
Network (GRU) and a Capsule Network based model for the task. Pre-trained word
embeddings have been utilized to incorporate contextual knowledge about words
into the model. GRU layer learns latent representations using the input word
embeddings. Subsequent Capsule Network layer learns high-level features from
that hidden representation. The proposed model managed to achieve a macro-F1
score of 0.692.
