@InProceedings{meisheri-EtAl:2017:WASSA2017,
  author    = {Meisheri, Hardik  and  Saha, Rupsa  and  Sinha, Priyanka  and  Dey, Lipika},
  title     = {Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets},
  booktitle = {Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {193--199},
  abstract  = {This paper describes our approach to the Emotion Intensity shared task. A
	parallel
	architecture of Convolutional Neural Network (CNN) and Long short term memory
	networks (LSTM) alongwith two sets of features are extracted which aid the
	network
	in judging emotion intensity. Experiments on different models and various
	features
	sets are described and analysis on results has also been presented.},
  url       = {http://www.aclweb.org/anthology/W17-5226}
}