The paper describes the best performing system for EmoInt - a shared task to pre- dict the intensity of emotions in tweets. Intensity is a real valued score, between 0 and 1. The emotions are classified as - anger, fear, joy and sadness. We ap- ply three different deep neural network based models, which approach the prob- lem from essentially different directions. Our final performance quantified by an av- erage pearson correlation score of 74.7 and an average spearman correlation score of 73.5 is obtained using an ensemble of the three models. We outperform the base- line model of the shared task by 9.9% and 9.4% pearson and spearman correla- tion scores respectively.
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