@InProceedings{pamnani-EtAl:2019:S19-2,
  author    = {Pamnani, Arik  and  Goel, Rajat  and  Choudhari, Jayesh  and  Singh, Mayank},
  title     = {IIT Gandhinagar at SemEval-2019 Task 3: Contextual Emotion Detection Using Deep Learning},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {236--240},
  abstract  = {Recent advancements in Internet and Mobile infrastructure have resulted in the development of faster and efficient platforms of communication. These platforms include speech, facial and text-based conversational mediums. Majority of these are text-based messaging platforms. Development of Chatbots that automatically understand latent emotions in the textual message is a challenging task. In this paper, we present an automatic emotion detection system that aims to detect the emotion of a person textually conversing with a chatbot. We explore deep learning techniques such as CNN and LSTM based neural networks and outperformed the baseline score by 14\%. The trained model and code are kept in public domain.},
  url       = {http://www.aclweb.org/anthology/S19-2039}
}