@InProceedings{khosla:2018:SocialNLP2018,
  author    = {Khosla, Sopan},
  title     = {EmotionX-AR: CNN-DCNN autoencoder based Emotion Classifier},
  booktitle = {Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {37--44},
  abstract  = {In this paper, we model emotions in EmotionLines dataset using a convolutional-deconvolutional autoencoder (CNN-DCNN) framework. We show that adding a joint reconstruction loss improves performance. Quantitative evaluation with jointly trained network, augmented with linguistic features, reports best accuracies for emotion prediction; namely joy, sadness, anger, and neutral emotion in text.},
  url       = {http://www.aclweb.org/anthology/W18-3507}
}