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In this paper, we propose a deep learning system for classification of tweets on a two-point scale. Our architecture consists of a multilayered recurrent neural network having gated recurrent units. The network is pre-trained with a weakly labeled dataset of tweets to learn the sentiment specific embeddings. Then it is fine tuned on the given training dataset of the task 4B in SemEval-2016. The network does very little pre-processing for raw tweets and no post-processing at all. The proposed system achieves 3rd rank on the leaderboard of task 4B.

thecerealkiller at SemEval-2016 Task 4: Deep Learning based System for Classifying Sentiment of Tweets on Two Point Scale