Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets

• Pranav Goel ^[1] ; Devang Kulshreshtha ^[1] ; Prayas Jain ^[1] ; K.K. Shukla ^[1]
  1. [1] Indian Institute of Technology (Banaras Hindu University) Varanasi, India
• Localización: 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA 2017: Proceedings of the Workshop / Alexandra Balahur Dobrescu (ed. lit.), Saif M. Mohammad (ed. lit.), Erik van der Goot (ed. lit.), 2017, ISBN 978-1-945626-95-1, págs. 58-65
• Idioma: inglés
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  • 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.